#catboost

Alberto Sánchez-Pascuala

@albertospj.bsky.social

2 weeks ago

🚀 Just finished the Kaggle House Prices challenge!
#CatBoost model, RMSE 0.0744, ranked ~700 worldwide among thousands of participants. 💻🏠
Super happy with this result and ready to keep learning! #MachineLearning #DataScience #Python
#kaggle - kaggle.com/competitions...

Hashlytics.io

@hashlytics.io

1 month ago

CatBoost ML Algorithm Boosts Cloud DDoS Detection Accuracy

Distributed Denial of Service (DDoS) attacks continue to threaten cloud infrastructure, causing service disruptions, data loss, and financial damage. As... #CatBoost

Herbert Chang 張賀鈞

@herbertchang.bsky.social

5 months ago

This study was powered by #CatBoost, a machine learning model whose name was too perfect to pass up 🐱
Paper also available here: www.herbert-chang.com/researchport...

Valeriy M., PhD, MBA, CQF

@predict-addict.bsky.social

6 months ago

🚀 Mastering CatBoost: The Hidden Gem of Tabular AI (Early Release Preorder) 🛒 Pre‑Order Details Incremental chapter release: Chapters are released gradually. As content drops, both the value and price climb over time. Lifetime updates included: By preordering now, you’ll receive every current and future update for the book at no extra cost. By Valeriy Manokhin, PhD, MBA, CQF “CatBoost is not just underrated—it’s objectively better.”This book shows you why, with the science and the code to prove it. 💸 Pricing 🎉 Launch Price: $30 | Minimum: $25Will increase to $60+ as content grows. As the content continues to grow, if you find value in it—or simply want to support the project—you're welcome to contribute whatever it’s worth to you ❤️. 🧠 Why CatBoost?There’s a preponderance of scientific evidence that CatBoost consistently and significantly (20%+ according to TabArena outperforms XGBoost, and LightGBM on real-world tabular data.It's faster in inference, easier to tune, and built from the ground up for categorical features—without the usual preprocessing hacks.Despite this, CatBoost remains one of the most underused tools in machine learning. This book fixes that.🧪 Backed by research, benchmarks, and production experience📈 Practical, readable, hands-on for working data scientists🔬 Linked to the open-source repo: Awesome CatBoost🔍 What You’ll Learn Core architecture: how CatBoost works under the hood Hands-on modeling: end-to-end tabular ML pipelines Categorical encoding: no more label/one-hot hacks Overfitting detection: built-in, automated safeguards Evaluation strategies: cross-validation the CatBoost way Interpretability: SHAP, feature importance, monotonic constraints Bonus: Time series with CatBoost + quantile & uncertainty modeling 📘 Scope & Depth: More than Just Boosters Mastering CatBoost covers: Not just classification, but regression, ranking, time series, and even quantile/uncertainty models Deep dive into categorical feature handling (CatBoost’s core advantage) Native overfitting detection, monotonic constraints, and interpretability tools all built-in and tuned for tabular workflows 🏗️ Under-the-Hood Architecture & Scientific Advantages Harrison’s book provides intuition and tuning advice, with code examples and deployment workflows . Mastering CatBoost delves into: Ordered boosting, symmetric trees, and smoothed target statistics — explaining why CatBoost handles categorical variables without leakage Scientific benchmarks consistently show CatBoost outperforming XGBoost and LightGBM on real-world tabular datasets Includes newer capabilities like GPU optimizations, quantization, and ONNX export 🧩 Interpretability & Safeguards Native overfitting detection, eliminating guesswork Built-in per-feature importance, interaction, and partial dependence tools Monotonic constraints tuned specifically for CatBoost internals 🎯 The Verdict Mastering CatBoost goes far beyond: In technical depth (architecture + categorical handling) Applied scope (classification, regression, ranking, forecasting) Deployment readiness (quantization, ONNX, real-world pipelines) Support materials (Awesome_CatBoost repo, notebooks, domain-specific chapters) 👨‍💻 Who Is This For?This book is designed for: Machine learning engineers using tabular datasets Data scientists tired of endless hyperparameter tuning Students or researchers who’ve hit limits with XGBoost or sklearn Practitioners who want to move fast from data to insight If you like fast iteration, fewer bugs, and state-of-the-art tabular models, this book is for you.📦 What You Get📥 Instant access to the book — start reading immediately.🔄 Free updates — including new chapters, bug fixes, and bonus content.💬 Exclusive access to the private Discord community — connect with fellow readers, get additional materials, early bonuses, special discounts, and join live events with the author.🔓 Pro Edition Bonus Pack (Early Access – $60) 🔥🔥🔥 Includes everything above, plus:✅ Premium Templates — plug-and-play workflows✅ Extended Case Studies — deep analyses across major industries✅ Cheat Sheets & Flashcards — quick-reference model guides and best practices✅ Behind-the-Scenes Notebooks — annotated walkthroughs and exploratory pipelines✅ Tabular Model Selection Toolkit — Python notebooks to benchmark, optimize, and compare📈 Ideal for professionals and teams who want to build and deploy faster—and sidestep the guesswork.✍️ About the AuthorWritten by Valeriy Manokhin, PhD, MBA, CQF — a seasoned forecasting expert, data scientist, and machine learning researcher with publications in top academic journals.Valeriy has advised both startups and large enterprises, helping them build and rebuild forecasting systems at scale. He has led successful forecasting initiatives for global organizations — including winning competitive tenders from multinational companies, outperforming major consulting firms like BCG and specialized AI startups focused on forecasting. He has delivered production-grade solutions for industry leaders such as Stanley Black & Decker and GfK.His methods have driven multimillion-dollar business impact, and his training programs have reached professionals in over 40 countries. This book is now used in more than 100+ countries and has become a #1-ranked title in Machine Learning, Forecasting, and Time Series across major platforms.🌍 Trusted By and Taught ToValeriy’s expertise is trusted by leaders at:Amazon, Apple, Google, Meta, Nike, BlackRock, Morgan Stanley, Target, NTT Data, Mars Inc., Lidl, Publicis Sapient, and more.His frameworks are followed by professionals from:University of Chicago, KTH (Sweden), UBC (Canada), DTU (Denmark), and other world-class institutions.👤 Students include:VPs of Engineering, AI Leads, Principal & Lead Data Scientists, ML Engineers, Consultants, Professors, Founders, Researchers, and PhD students.📚 Also by the AuthorMastering Modern Time Series ForecastingThe book trusted by data science leaders in 100+ countries. Unlock the toolkit behind today’s most powerful forecasting systems.Learn more → MasteringModernTimeSeriesForecasting⚡ Ready to Master the Best Tabular Model in ML?CatBoost isn’t just another gradient booster.It’s the most underappreciated breakthrough in machine learning—and you’re about to master it.👉 Grab your copy now and start building faster, better models with less tuning.

If you work with tabular data, this is your unfair advantage. Preorder now.

valeman.gumroad.com/...

#MachineLearning #DataScience #CatBoost #XGBoost #Kaggle #GradientBoosting #AI #MLEngineering #MasteringCatBoost

Valeriy M., PhD, MBA, CQF

@predict-addict.bsky.social

6 months ago

Whether you’re aiming to win Kaggle competitions, deploy robust models in production, or simply level up your ML toolkit, Mastering CatBoost will get you there.
#MachineLearning #DataScience #CatBoost #ML #AI #GradientBoosting #GBDT #Kaggle #Python #MLOps #TabularData #BookLaunch

Valeriy M., PhD, MBA, CQF

@predict-addict.bsky.social

6 months ago

Whether you’re aiming to win Kaggle competitions, deploy robust models in production, or simply level up your ML toolkit, Mastering CatBoost will get you there.
#MachineLearning #DataScience #CatBoost #ML #AI #GradientBoosting #GBDT #Kaggle #Python #MLOps #TabularData #BookLaunch

Valeriy M., PhD, MBA, CQF

@predict-addict.bsky.social

6 months ago

Whether you’re aiming to win Kaggle competitions, deploy robust models in production, or simply level up your ML toolkit, Mastering CatBoost will get you there.
#MachineLearning #DataScience #CatBoost #ML #AI #GradientBoosting #GBDT #Kaggle #Python #MLOps #TabularData #BookLaunch

Valeriy M., PhD, MBA, CQF

@predict-addict.bsky.social

6 months ago

🚀 Mastering CatBoost: The Hidden Gem of Tabular AI (Early Release Preorder) 🛒 Pre‑Order Details Incremental chapter release: Chapters are released gradually. As content drops, both the value and price climb over time. Lifetime updates included: By preordering now, you’ll receive every current and future update for the book at no extra cost. By Valeriy Manokhin, PhD, MBA, CQF “CatBoost is not just underrated—it’s objectively better.”This book shows you why, with the science and the code to prove it. 💸 Pricing 🎉 Launch Price: $30 | Minimum: $25Will increase to $60+ as content grows. As the content continues to grow, if you find value in it—or simply want to support the project—you're welcome to contribute whatever it’s worth to you ❤️. 🧠 Why CatBoost?There’s a preponderance of scientific evidence that CatBoost consistently and significantly (20%+ according to TabArena outperforms XGBoost, and LightGBM on real-world tabular data.It's faster in inference, easier to tune, and built from the ground up for categorical features—without the usual preprocessing hacks.Despite this, CatBoost remains one of the most underused tools in machine learning. This book fixes that.🧪 Backed by research, benchmarks, and production experience📈 Practical, readable, hands-on for working data scientists🔬 Linked to the open-source repo: Awesome CatBoost🔍 What You’ll Learn Core architecture: how CatBoost works under the hood Hands-on modeling: end-to-end tabular ML pipelines Categorical encoding: no more label/one-hot hacks Overfitting detection: built-in, automated safeguards Evaluation strategies: cross-validation the CatBoost way Interpretability: SHAP, feature importance, monotonic constraints Bonus: Time series with CatBoost + quantile & uncertainty modeling 📘 Scope & Depth: More than Just Boosters Mastering CatBoost covers: Not just classification, but regression, ranking, time series, and even quantile/uncertainty models Deep dive into categorical feature handling (CatBoost’s core advantage) Native overfitting detection, monotonic constraints, and interpretability tools all built-in and tuned for tabular workflows 🏗️ Under-the-Hood Architecture & Scientific Advantages Harrison’s book provides intuition and tuning advice, with code examples and deployment workflows . Mastering CatBoost delves into: Ordered boosting, symmetric trees, and smoothed target statistics — explaining why CatBoost handles categorical variables without leakage Scientific benchmarks consistently show CatBoost outperforming XGBoost and LightGBM on real-world tabular datasets Includes newer capabilities like GPU optimizations, quantization, and ONNX export 🧩 Interpretability & Safeguards Native overfitting detection, eliminating guesswork Built-in per-feature importance, interaction, and partial dependence tools Monotonic constraints tuned specifically for CatBoost internals 🎯 The Verdict Mastering CatBoost goes far beyond: In technical depth (architecture + categorical handling) Applied scope (classification, regression, ranking, forecasting) Deployment readiness (quantization, ONNX, real-world pipelines) Support materials (Awesome_CatBoost repo, notebooks, domain-specific chapters) 👨‍💻 Who Is This For?This book is designed for: Machine learning engineers using tabular datasets Data scientists tired of endless hyperparameter tuning Students or researchers who’ve hit limits with XGBoost or sklearn Practitioners who want to move fast from data to insight If you like fast iteration, fewer bugs, and state-of-the-art tabular models, this book is for you.📦 What You Get📥 Instant access to the book — start reading immediately.🔄 Free updates — including new chapters, bug fixes, and bonus content.💬 Exclusive access to the private Discord community — connect with fellow readers, get additional materials, early bonuses, special discounts, and join live events with the author.🔓 Pro Edition Bonus Pack (Early Access – $60) 🔥🔥🔥 Includes everything above, plus:✅ Premium Templates — plug-and-play workflows✅ Extended Case Studies — deep analyses across major industries✅ Cheat Sheets & Flashcards — quick-reference model guides and best practices✅ Behind-the-Scenes Notebooks — annotated walkthroughs and exploratory pipelines✅ Tabular Model Selection Toolkit — Python notebooks to benchmark, optimize, and compare📈 Ideal for professionals and teams who want to build and deploy faster—and sidestep the guesswork.✍️ About the AuthorWritten by Valeriy Manokhin, PhD, MBA, CQF — a seasoned forecasting expert, data scientist, and machine learning researcher with publications in top academic journals.Valeriy has advised both startups and large enterprises, helping them build and rebuild forecasting systems at scale. He has led successful forecasting initiatives for global organizations — including winning competitive tenders from multinational companies, outperforming major consulting firms like BCG and specialized AI startups focused on forecasting. He has delivered production-grade solutions for industry leaders such as Stanley Black & Decker and GfK.His methods have driven multimillion-dollar business impact, and his training programs have reached professionals in over 40 countries. This book is now used in more than 100+ countries and has become a #1-ranked title in Machine Learning, Forecasting, and Time Series across major platforms.🌍 Trusted By and Taught ToValeriy’s expertise is trusted by leaders at:Amazon, Apple, Google, Meta, Nike, BlackRock, Morgan Stanley, Target, NTT Data, Mars Inc., Lidl, Publicis Sapient, and more.His frameworks are followed by professionals from:University of Chicago, KTH (Sweden), UBC (Canada), DTU (Denmark), and other world-class institutions.👤 Students include:VPs of Engineering, AI Leads, Principal & Lead Data Scientists, ML Engineers, Consultants, Professors, Founders, Researchers, and PhD students.📚 Also by the AuthorMastering Modern Time Series ForecastingThe book trusted by data science leaders in 100+ countries. Unlock the toolkit behind today’s most powerful forecasting systems.Learn more → MasteringModernTimeSeriesForecasting⚡ Ready to Master the Best Tabular Model in ML?CatBoost isn’t just another gradient booster.It’s the most underappreciated breakthrough in machine learning—and you’re about to master it.👉 Grab your copy now and start building faster, better models with less tuning.

If you work with tabular data, this is your unfair advantage. Preorder now.

valeman.gumroad.com/...

#MachineLearning #DataScience #CatBoost #XGBoost #Kaggle #GradientBoosting #AI #MLEngineering #MasteringCatBoost

Valeriy M., PhD, MBA, CQF

@predict-addict.bsky.social

6 months ago

Whether you’re aiming to win Kaggle competitions, deploy robust models in production, or simply level up your ML toolkit, Mastering CatBoost will get you there.
#MachineLearning #DataScience #CatBoost #ML #AI #GradientBoosting #GBDT #Kaggle #Python #MLOps #TabularData #BookLaunch

Valeriy M., PhD, MBA, CQF

@predict-addict.bsky.social

6 months ago

🚀 Pro Edition → Book + Bonus Pack "Mastering CatBoost: The Hidden Gem of Tabular AI " (Early Release Preorder) 🔥 Pro Edition: "Mastering CatBoost: The Hidden Gem of Tabular AI" (Early Access) The elite version of the book — trusted by data science leaders in 100+ countries.Unlock the premium toolkit behind today’s most powerful model for tabular data. 🚀🚀🚀 New: Pro Edition Now Available — $60 (USD) 🔥🔥🔥Includes everything in the standard edition plus: premium templates, cheat sheets, extended case studies, behind‑the‑scenes notebooks, model tuning toolkits, and access to live Q&A + AMA sessions with the author.⚠️ Final price of Pro Edition will rise to $150+ at book completion. See 📦 What You Get and 💸 Pricing for full details. By Valeriy Manokhin, PhD, MBA, CQF “CatBoost is not just underrated—it’s objectively better.”This book shows you why, with the science and the code to prove it. 🔓 Pro Edition Bonus Pack (Early Access – $60) Includes everything above, plus: ✅ Premium Templates — plug-and-play workflows✅ Extended Case Studies — deep analyses across major industries✅ Cheat Sheets & Flashcards — quick-reference model guides and best practices✅ Behind-the-Scenes Notebooks — annotated walkthroughs and exploratory pipelines✅ Model Selection Toolkit — Python notebooks to benchmark, optimize, and compare 📈 Ideal for professionals and teams who want to build and deploy faster—and sidestep the guesswork. 💸 Pricing 🚀 Pro Edition Early Access: Price: $70 | Minimum: $60Includes the full book + Premium Pack.✅ Lock in now—price will rise to $150+ at full release. As the content continues to grow, if you find value in it—or simply want to support the project—you're welcome to contribute whatever it’s worth to you ❤️. Ready to take your tabular machine learning skills to next level? 👉 Hit Buy Now, and if you want structured support, check out the course at 🧠 Why CatBoost? There’s a preponderance of scientific evidence that CatBoost consistently and significantly (20%+ according to TabArena outperforms XGBoost, and LightGBM on real-world tabular data.It's faster in inference, easier to tune, and built from the ground up for categorical features—without the usual preprocessing hacks.Despite this, CatBoost remains one of the most underused tools in machine learning. This book fixes that.🧪 Backed by research, benchmarks, and production experience📈 Practical, readable, hands-on for working data scientists🔬 Linked to the open-source repo: Awesome CatBoost🔍 What You’ll Learn Core architecture: how CatBoost works under the hood Hands-on modeling: end-to-end tabular ML pipelines Categorical encoding: no more label/one-hot hacks Overfitting detection: built-in, automated safeguards Evaluation strategies: cross-validation the CatBoost way Interpretability: SHAP, feature importance, monotonic constraints Bonus: Time series with CatBoost + quantile & uncertainty modeling 📘 Scope & Depth: More than Just Boosters Mastering CatBoost covers: Not just classification, but regression, ranking, time series, and even quantile/uncertainty models Deep dive into categorical feature handling (CatBoost’s core advantage) Native overfitting detection, monotonic constraints, and interpretability tools all built-in and tuned for tabular workflows 🏗️ Under-the-Hood Architecture & Scientific Advantages Harrison’s book provides intuition and tuning advice, with code examples and deployment workflows . Mastering CatBoost delves into: Ordered boosting, symmetric trees, and smoothed target statistics — explaining why CatBoost handles categorical variables without leakage Scientific benchmarks consistently show CatBoost outperforming XGBoost and LightGBM on real-world tabular datasets Includes newer capabilities like GPU optimizations, quantization, and ONNX export 🧩 Interpretability & Safeguards Native overfitting detection, eliminating guesswork Built-in per-feature importance, interaction, and partial dependence tools Monotonic constraints tuned specifically for CatBoost internals 🎯 The Verdict Mastering CatBoost goes far beyond: In technical depth (architecture + categorical handling) Applied scope (classification, regression, ranking, forecasting) Deployment readiness (quantization, ONNX, real-world pipelines) Support materials (Awesome_CatBoost repo, notebooks, domain-specific chapters) 👨‍💻 Who Is This For?This book is designed for: Machine learning engineers using tabular datasets Data scientists tired of endless hyperparameter tuning Students or researchers who’ve hit limits with XGBoost or sklearn Practitioners who want to move fast from data to insight If you like fast iteration, fewer bugs, and state-of-the-art tabular models, this book is for you.📦 What You Get📥 Instant access to the book — start reading immediately.🔄 Free updates — including new chapters, bug fixes, and bonus content.💬 Exclusive access to the private Discord community — connect with fellow readers, get additional materials, early bonuses, special discounts, and join live events with the author.🔓 Pro Edition Bonus Pack (Early Access – $60) 🔥🔥🔥 Includes everything above, plus:✅ Premium Templates — plug-and-play workflows✅ Extended Case Studies — deep analyses across major industries✅ Cheat Sheets & Flashcards — quick-reference model guides and best practices✅ Behind-the-Scenes Notebooks — annotated walkthroughs and exploratory pipelines✅ Tabular Model Selection Toolkit — Python notebooks to benchmark, optimize, and compare📈 Ideal for professionals and teams who want to build and deploy faster—and sidestep the guesswork.✍️ About the AuthorWritten by Valeriy Manokhin, PhD, MBA, CQF — a seasoned forecasting expert, data scientist, and machine learning researcher with publications in top academic journals.Valeriy has advised both startups and large enterprises, helping them build and rebuild forecasting systems at scale. He has led successful forecasting initiatives for global organizations — including winning competitive tenders from multinational companies, outperforming major consulting firms like BCG and specialized AI startups focused on forecasting. He has delivered production-grade solutions for industry leaders such as Stanley Black & Decker and GfK.His methods have driven multimillion-dollar business impact, and his training programs have reached professionals in over 40 countries. This book is now used in more than 100+ countries and has become a #1-ranked title in Machine Learning, Forecasting, and Time Series across major platforms.🌍 Trusted By and Taught ToValeriy’s expertise is trusted by leaders at:Amazon, Apple, Google, Meta, Nike, BlackRock, Morgan Stanley, Target, NTT Data, Mars Inc., Lidl, Publicis Sapient, and more.His frameworks are followed by professionals from:University of Chicago, KTH (Sweden), UBC (Canada), DTU (Denmark), and other world-class institutions.👤 Students include:VPs of Engineering, AI Leads, Principal & Lead Data Scientists, ML Engineers, Consultants, Professors, Founders, Researchers, and PhD students.📚 Also by the AuthorMastering Modern Time Series ForecastingThe book trusted by data science leaders in 100+ countries. Unlock the toolkit behind today’s most powerful forecasting systems.Learn more → MasteringModernTimeSeriesForecasting⚡ Ready to Master the Best Tabular Model in ML?CatBoost isn’t just another gradient booster.It’s the most underappreciated breakthrough in machine learning—and you’re about to master it.👉 Grab your copy now and start building faster, better models with less tuning.

Mastering CatBoost Pro -> valeman.gumroad.com/...

valeman.gumroad.com/...

#tabulardata #catboost #ai #xgboost

Valeriy M., PhD, MBA, CQF

@predict-addict.bsky.social

6 months ago

🚀 Mastering CatBoost: The Hidden Gem of Tabular AI (Early Release Preorder) 🛒 Pre‑Order Details Incremental chapter release: Chapters are released gradually. As content drops, both the value and price climb over time. Lifetime updates included: By preordering now, you’ll receive every current and future update for the book at no extra cost. By Valeriy Manokhin, PhD, MBA, CQF “CatBoost is not just underrated—it’s objectively better.”This book shows you why, with the science and the code to prove it. 💸 Pricing 🎉 Launch Price: $30 | Minimum: $25Will increase to $60+ as content grows. As the content continues to grow, if you find value in it—or simply want to support the project—you're welcome to contribute whatever it’s worth to you ❤️. 🧠 Why CatBoost?There’s a preponderance of scientific evidence that CatBoost consistently and significantly (20%+ according to TabArena outperforms XGBoost, and LightGBM on real-world tabular data.It's faster in inference, easier to tune, and built from the ground up for categorical features—without the usual preprocessing hacks.Despite this, CatBoost remains one of the most underused tools in machine learning. This book fixes that.🧪 Backed by research, benchmarks, and production experience📈 Practical, readable, hands-on for working data scientists🔬 Linked to the open-source repo: Awesome CatBoost🔍 What You’ll Learn Core architecture: how CatBoost works under the hood Hands-on modeling: end-to-end tabular ML pipelines Categorical encoding: no more label/one-hot hacks Overfitting detection: built-in, automated safeguards Evaluation strategies: cross-validation the CatBoost way Interpretability: SHAP, feature importance, monotonic constraints Bonus: Time series with CatBoost + quantile & uncertainty modeling 📘 Scope & Depth: More than Just Boosters Mastering CatBoost covers: Not just classification, but regression, ranking, time series, and even quantile/uncertainty models Deep dive into categorical feature handling (CatBoost’s core advantage) Native overfitting detection, monotonic constraints, and interpretability tools all built-in and tuned for tabular workflows 🏗️ Under-the-Hood Architecture & Scientific Advantages Harrison’s book provides intuition and tuning advice, with code examples and deployment workflows . Mastering CatBoost delves into: Ordered boosting, symmetric trees, and smoothed target statistics — explaining why CatBoost handles categorical variables without leakage Scientific benchmarks consistently show CatBoost outperforming XGBoost and LightGBM on real-world tabular datasets Includes newer capabilities like GPU optimizations, quantization, and ONNX export 🧩 Interpretability & Safeguards Native overfitting detection, eliminating guesswork Built-in per-feature importance, interaction, and partial dependence tools Monotonic constraints tuned specifically for CatBoost internals 🎯 The Verdict Mastering CatBoost goes far beyond: In technical depth (architecture + categorical handling) Applied scope (classification, regression, ranking, forecasting) Deployment readiness (quantization, ONNX, real-world pipelines) Support materials (Awesome_CatBoost repo, notebooks, domain-specific chapters) 👨‍💻 Who Is This For?This book is designed for: Machine learning engineers using tabular datasets Data scientists tired of endless hyperparameter tuning Students or researchers who’ve hit limits with XGBoost or sklearn Practitioners who want to move fast from data to insight If you like fast iteration, fewer bugs, and state-of-the-art tabular models, this book is for you.📦 What You Get📥 Instant access to the book — start reading immediately.🔄 Free updates — including new chapters, bug fixes, and bonus content.💬 Exclusive access to the private Discord community — connect with fellow readers, get additional materials, early bonuses, special discounts, and join live events with the author.🔓 Pro Edition Bonus Pack (Early Access – $60) 🔥🔥🔥 Includes everything above, plus:✅ Premium Templates — plug-and-play workflows✅ Extended Case Studies — deep analyses across major industries✅ Cheat Sheets & Flashcards — quick-reference model guides and best practices✅ Behind-the-Scenes Notebooks — annotated walkthroughs and exploratory pipelines✅ Tabular Model Selection Toolkit — Python notebooks to benchmark, optimize, and compare📈 Ideal for professionals and teams who want to build and deploy faster—and sidestep the guesswork.✍️ About the AuthorWritten by Valeriy Manokhin, PhD, MBA, CQF — a seasoned forecasting expert, data scientist, and machine learning researcher with publications in top academic journals.Valeriy has advised both startups and large enterprises, helping them build and rebuild forecasting systems at scale. He has led successful forecasting initiatives for global organizations — including winning competitive tenders from multinational companies, outperforming major consulting firms like BCG and specialized AI startups focused on forecasting. He has delivered production-grade solutions for industry leaders such as Stanley Black & Decker and GfK.His methods have driven multimillion-dollar business impact, and his training programs have reached professionals in over 40 countries. This book is now used in more than 100+ countries and has become a #1-ranked title in Machine Learning, Forecasting, and Time Series across major platforms.🌍 Trusted By and Taught ToValeriy’s expertise is trusted by leaders at:Amazon, Apple, Google, Meta, Nike, BlackRock, Morgan Stanley, Target, NTT Data, Mars Inc., Lidl, Publicis Sapient, and more.His frameworks are followed by professionals from:University of Chicago, KTH (Sweden), UBC (Canada), DTU (Denmark), and other world-class institutions.👤 Students include:VPs of Engineering, AI Leads, Principal & Lead Data Scientists, ML Engineers, Consultants, Professors, Founders, Researchers, and PhD students.📚 Also by the AuthorMastering Modern Time Series ForecastingThe book trusted by data science leaders in 100+ countries. Unlock the toolkit behind today’s most powerful forecasting systems.Learn more → MasteringModernTimeSeriesForecasting⚡ Ready to Master the Best Tabular Model in ML?CatBoost isn’t just another gradient booster.It’s the most underappreciated breakthrough in machine learning—and you’re about to master it.👉 Grab your copy now and start building faster, better models with less tuning.

If you work with tabular data, this is your unfair advantage. Preorder now.

valeman.gumroad.com/...

#MachineLearning #DataScience #CatBoost #XGBoost #Kaggle #GradientBoosting #AI #MLEngineering #MasteringCatBoost

Valeriy M., PhD, MBA, CQF

@predict-addict.bsky.social

6 months ago

Whether you’re aiming to win Kaggle competitions, deploy robust models in production, or simply level up your ML toolkit, Mastering CatBoost will get you there.
#MachineLearning #DataScience #CatBoost #ML #AI #GradientBoosting #GBDT #Kaggle #Python #MLOps #TabularData #BookLaunch

Valeriy M., PhD, MBA, CQF

@predict-addict.bsky.social

6 months ago

🚀 Mastering CatBoost: The Hidden Gem of Tabular AI (Early Release Preorder) 🛒 Pre‑Order Details Incremental chapter release: Chapters are released gradually. As content drops, both the value and price climb over time. Lifetime updates included: By preordering now, you’ll receive every current and future update for the book at no extra cost. By Valeriy Manokhin, PhD, MBA, CQF “CatBoost is not just underrated—it’s objectively better.”This book shows you why, with the science and the code to prove it. 💸 Pricing 🎉 Launch Price: $30 | Minimum: $25Will increase to $60+ as content grows. As the content continues to grow, if you find value in it—or simply want to support the project—you're welcome to contribute whatever it’s worth to you ❤️. 🧠 Why CatBoost?There’s a preponderance of scientific evidence that CatBoost consistently and significantly (20%+ according to TabArena outperforms XGBoost, and LightGBM on real-world tabular data.It's faster in inference, easier to tune, and built from the ground up for categorical features—without the usual preprocessing hacks.Despite this, CatBoost remains one of the most underused tools in machine learning. This book fixes that.🧪 Backed by research, benchmarks, and production experience📈 Practical, readable, hands-on for working data scientists🔬 Linked to the open-source repo: Awesome CatBoost🔍 What You’ll Learn Core architecture: how CatBoost works under the hood Hands-on modeling: end-to-end tabular ML pipelines Categorical encoding: no more label/one-hot hacks Overfitting detection: built-in, automated safeguards Evaluation strategies: cross-validation the CatBoost way Interpretability: SHAP, feature importance, monotonic constraints Bonus: Time series with CatBoost + quantile & uncertainty modeling 📘 Scope & Depth: More than Just Boosters Mastering CatBoost covers: Not just classification, but regression, ranking, time series, and even quantile/uncertainty models Deep dive into categorical feature handling (CatBoost’s core advantage) Native overfitting detection, monotonic constraints, and interpretability tools all built-in and tuned for tabular workflows 🏗️ Under-the-Hood Architecture & Scientific Advantages Harrison’s book provides intuition and tuning advice, with code examples and deployment workflows . Mastering CatBoost delves into: Ordered boosting, symmetric trees, and smoothed target statistics — explaining why CatBoost handles categorical variables without leakage Scientific benchmarks consistently show CatBoost outperforming XGBoost and LightGBM on real-world tabular datasets Includes newer capabilities like GPU optimizations, quantization, and ONNX export 🧩 Interpretability & Safeguards Native overfitting detection, eliminating guesswork Built-in per-feature importance, interaction, and partial dependence tools Monotonic constraints tuned specifically for CatBoost internals 🎯 The Verdict Mastering CatBoost goes far beyond: In technical depth (architecture + categorical handling) Applied scope (classification, regression, ranking, forecasting) Deployment readiness (quantization, ONNX, real-world pipelines) Support materials (Awesome_CatBoost repo, notebooks, domain-specific chapters) 👨‍💻 Who Is This For?This book is designed for: Machine learning engineers using tabular datasets Data scientists tired of endless hyperparameter tuning Students or researchers who’ve hit limits with XGBoost or sklearn Practitioners who want to move fast from data to insight If you like fast iteration, fewer bugs, and state-of-the-art tabular models, this book is for you.📦 What You Get📥 Instant access to the book — start reading immediately.🔄 Free updates — including new chapters, bug fixes, and bonus content.💬 Exclusive access to the private Discord community — connect with fellow readers, get additional materials, early bonuses, special discounts, and join live events with the author.🔓 Pro Edition Bonus Pack (Early Access – $60) 🔥🔥🔥 Includes everything above, plus:✅ Premium Templates — plug-and-play workflows✅ Extended Case Studies — deep analyses across major industries✅ Cheat Sheets & Flashcards — quick-reference model guides and best practices✅ Behind-the-Scenes Notebooks — annotated walkthroughs and exploratory pipelines✅ Tabular Model Selection Toolkit — Python notebooks to benchmark, optimize, and compare📈 Ideal for professionals and teams who want to build and deploy faster—and sidestep the guesswork.✍️ About the AuthorWritten by Valeriy Manokhin, PhD, MBA, CQF — a seasoned forecasting expert, data scientist, and machine learning researcher with publications in top academic journals.Valeriy has advised both startups and large enterprises, helping them build and rebuild forecasting systems at scale. He has led successful forecasting initiatives for global organizations — including winning competitive tenders from multinational companies, outperforming major consulting firms like BCG and specialized AI startups focused on forecasting. He has delivered production-grade solutions for industry leaders such as Stanley Black & Decker and GfK.His methods have driven multimillion-dollar business impact, and his training programs have reached professionals in over 40 countries. This book is now used in more than 100+ countries and has become a #1-ranked title in Machine Learning, Forecasting, and Time Series across major platforms.🌍 Trusted By and Taught ToValeriy’s expertise is trusted by leaders at:Amazon, Apple, Google, Meta, Nike, BlackRock, Morgan Stanley, Target, NTT Data, Mars Inc., Lidl, Publicis Sapient, and more.His frameworks are followed by professionals from:University of Chicago, KTH (Sweden), UBC (Canada), DTU (Denmark), and other world-class institutions.👤 Students include:VPs of Engineering, AI Leads, Principal & Lead Data Scientists, ML Engineers, Consultants, Professors, Founders, Researchers, and PhD students.📚 Also by the AuthorMastering Modern Time Series ForecastingThe book trusted by data science leaders in 100+ countries. Unlock the toolkit behind today’s most powerful forecasting systems.Learn more → MasteringModernTimeSeriesForecasting⚡ Ready to Master the Best Tabular Model in ML?CatBoost isn’t just another gradient booster.It’s the most underappreciated breakthrough in machine learning—and you’re about to master it.👉 Grab your copy now and start building faster, better models with less tuning.

Mastering CatBoost -> valeman.gumroad.com/...

Mastering CatBoost Pro -> valeman.gumroad.com/...

#MachineLearning #CatBoost #AI #MarkovChains #Boosting

Valeriy M., PhD, MBA, CQF

@predict-addict.bsky.social

6 months ago

🚀 Mastering CatBoost: The Hidden Gem of Tabular AI (Early Release Preorder) 🛒 Pre‑Order Details Incremental chapter release: Chapters are released gradually. As content drops, both the value and price climb over time. Lifetime updates included: By preordering now, you’ll receive every current and future update for the book at no extra cost. By Valeriy Manokhin, PhD, MBA, CQF “CatBoost is not just underrated—it’s objectively better.”This book shows you why, with the science and the code to prove it. 💸 Pricing 🎉 Launch Price: $30 | Minimum: $25Will increase to $60+ as content grows. As the content continues to grow, if you find value in it—or simply want to support the project—you're welcome to contribute whatever it’s worth to you ❤️. 🧠 Why CatBoost?There’s a preponderance of scientific evidence that CatBoost consistently and significantly (20%+ according to TabArena outperforms XGBoost, and LightGBM on real-world tabular data.It's faster in inference, easier to tune, and built from the ground up for categorical features—without the usual preprocessing hacks.Despite this, CatBoost remains one of the most underused tools in machine learning. This book fixes that.🧪 Backed by research, benchmarks, and production experience📈 Practical, readable, hands-on for working data scientists🔬 Linked to the open-source repo: Awesome CatBoost🔍 What You’ll Learn Core architecture: how CatBoost works under the hood Hands-on modeling: end-to-end tabular ML pipelines Categorical encoding: no more label/one-hot hacks Overfitting detection: built-in, automated safeguards Evaluation strategies: cross-validation the CatBoost way Interpretability: SHAP, feature importance, monotonic constraints Bonus: Time series with CatBoost + quantile & uncertainty modeling 📘 Scope & Depth: More than Just Boosters Mastering CatBoost covers: Not just classification, but regression, ranking, time series, and even quantile/uncertainty models Deep dive into categorical feature handling (CatBoost’s core advantage) Native overfitting detection, monotonic constraints, and interpretability tools all built-in and tuned for tabular workflows 🏗️ Under-the-Hood Architecture & Scientific Advantages Harrison’s book provides intuition and tuning advice, with code examples and deployment workflows . Mastering CatBoost delves into: Ordered boosting, symmetric trees, and smoothed target statistics — explaining why CatBoost handles categorical variables without leakage Scientific benchmarks consistently show CatBoost outperforming XGBoost and LightGBM on real-world tabular datasets Includes newer capabilities like GPU optimizations, quantization, and ONNX export 🧩 Interpretability & Safeguards Native overfitting detection, eliminating guesswork Built-in per-feature importance, interaction, and partial dependence tools Monotonic constraints tuned specifically for CatBoost internals 🎯 The Verdict Mastering CatBoost goes far beyond: In technical depth (architecture + categorical handling) Applied scope (classification, regression, ranking, forecasting) Deployment readiness (quantization, ONNX, real-world pipelines) Support materials (Awesome_CatBoost repo, notebooks, domain-specific chapters) 👨‍💻 Who Is This For?This book is designed for: Machine learning engineers using tabular datasets Data scientists tired of endless hyperparameter tuning Students or researchers who’ve hit limits with XGBoost or sklearn Practitioners who want to move fast from data to insight If you like fast iteration, fewer bugs, and state-of-the-art tabular models, this book is for you.📦 What You Get📥 Instant access to the book — start reading immediately.🔄 Free updates — including new chapters, bug fixes, and bonus content.💬 Exclusive access to the private Discord community — connect with fellow readers, get additional materials, early bonuses, special discounts, and join live events with the author.🔓 Pro Edition Bonus Pack (Early Access – $60) 🔥🔥🔥 Includes everything above, plus:✅ Premium Templates — plug-and-play workflows✅ Extended Case Studies — deep analyses across major industries✅ Cheat Sheets & Flashcards — quick-reference model guides and best practices✅ Behind-the-Scenes Notebooks — annotated walkthroughs and exploratory pipelines✅ Tabular Model Selection Toolkit — Python notebooks to benchmark, optimize, and compare📈 Ideal for professionals and teams who want to build and deploy faster—and sidestep the guesswork.✍️ About the AuthorWritten by Valeriy Manokhin, PhD, MBA, CQF — a seasoned forecasting expert, data scientist, and machine learning researcher with publications in top academic journals.Valeriy has advised both startups and large enterprises, helping them build and rebuild forecasting systems at scale. He has led successful forecasting initiatives for global organizations — including winning competitive tenders from multinational companies, outperforming major consulting firms like BCG and specialized AI startups focused on forecasting. He has delivered production-grade solutions for industry leaders such as Stanley Black & Decker and GfK.His methods have driven multimillion-dollar business impact, and his training programs have reached professionals in over 40 countries. This book is now used in more than 100+ countries and has become a #1-ranked title in Machine Learning, Forecasting, and Time Series across major platforms.🌍 Trusted By and Taught ToValeriy’s expertise is trusted by leaders at:Amazon, Apple, Google, Meta, Nike, BlackRock, Morgan Stanley, Target, NTT Data, Mars Inc., Lidl, Publicis Sapient, and more.His frameworks are followed by professionals from:University of Chicago, KTH (Sweden), UBC (Canada), DTU (Denmark), and other world-class institutions.👤 Students include:VPs of Engineering, AI Leads, Principal & Lead Data Scientists, ML Engineers, Consultants, Professors, Founders, Researchers, and PhD students.📚 Also by the AuthorMastering Modern Time Series ForecastingThe book trusted by data science leaders in 100+ countries. Unlock the toolkit behind today’s most powerful forecasting systems.Learn more → MasteringModernTimeSeriesForecasting⚡ Ready to Master the Best Tabular Model in ML?CatBoost isn’t just another gradient booster.It’s the most underappreciated breakthrough in machine learning—and you’re about to master it.👉 Grab your copy now and start building faster, better models with less tuning.

👉 Mastering CatBoost -> valeman.gumroad.com/...
And if you’re ready for the ultimate meow-level boost, go Pro:
👉 Mastering CatBoost Pro -> valeman.gumroad.com/...

Let’s stop overcomplicating and start building smarter models.
#DataScience #MachineLearning #CatBoost #AI #ML

Valeriy M., PhD, MBA, CQF

@predict-addict.bsky.social

6 months ago

🚀 Mastering CatBoost: The Hidden Gem of Tabular AI (Early Release Preorder) 🛒 Pre‑Order Details Incremental chapter release: Chapters are released gradually. As content drops, both the value and price climb over time. Lifetime updates included: By preordering now, you’ll receive every current and future update for the book at no extra cost. By Valeriy Manokhin, PhD, MBA, CQF “CatBoost is not just underrated—it’s objectively better.”This book shows you why, with the science and the code to prove it. 💸 Pricing 🎉 Launch Price: $30 | Minimum: $25Will increase to $60+ as content grows. As the content continues to grow, if you find value in it—or simply want to support the project—you're welcome to contribute whatever it’s worth to you ❤️. 🧠 Why CatBoost?There’s a preponderance of scientific evidence that CatBoost consistently and significantly (20%+ according to TabArena outperforms XGBoost, and LightGBM on real-world tabular data.It's faster in inference, easier to tune, and built from the ground up for categorical features—without the usual preprocessing hacks.Despite this, CatBoost remains one of the most underused tools in machine learning. This book fixes that.🧪 Backed by research, benchmarks, and production experience📈 Practical, readable, hands-on for working data scientists🔬 Linked to the open-source repo: Awesome CatBoost🔍 What You’ll Learn Core architecture: how CatBoost works under the hood Hands-on modeling: end-to-end tabular ML pipelines Categorical encoding: no more label/one-hot hacks Overfitting detection: built-in, automated safeguards Evaluation strategies: cross-validation the CatBoost way Interpretability: SHAP, feature importance, monotonic constraints Bonus: Time series with CatBoost + quantile & uncertainty modeling 📘 Scope & Depth: More than Just Boosters Mastering CatBoost covers: Not just classification, but regression, ranking, time series, and even quantile/uncertainty models Deep dive into categorical feature handling (CatBoost’s core advantage) Native overfitting detection, monotonic constraints, and interpretability tools all built-in and tuned for tabular workflows 🏗️ Under-the-Hood Architecture & Scientific Advantages Harrison’s book provides intuition and tuning advice, with code examples and deployment workflows . Mastering CatBoost delves into: Ordered boosting, symmetric trees, and smoothed target statistics — explaining why CatBoost handles categorical variables without leakage Scientific benchmarks consistently show CatBoost outperforming XGBoost and LightGBM on real-world tabular datasets Includes newer capabilities like GPU optimizations, quantization, and ONNX export 🧩 Interpretability & Safeguards Native overfitting detection, eliminating guesswork Built-in per-feature importance, interaction, and partial dependence tools Monotonic constraints tuned specifically for CatBoost internals 🎯 The Verdict Mastering CatBoost goes far beyond: In technical depth (architecture + categorical handling) Applied scope (classification, regression, ranking, forecasting) Deployment readiness (quantization, ONNX, real-world pipelines) Support materials (Awesome_CatBoost repo, notebooks, domain-specific chapters) 👨‍💻 Who Is This For?This book is designed for: Machine learning engineers using tabular datasets Data scientists tired of endless hyperparameter tuning Students or researchers who’ve hit limits with XGBoost or sklearn Practitioners who want to move fast from data to insight If you like fast iteration, fewer bugs, and state-of-the-art tabular models, this book is for you.📦 What You Get📥 Instant access to the book — start reading immediately.🔄 Free updates — including new chapters, bug fixes, and bonus content.💬 Exclusive access to the private Discord community — connect with fellow readers, get additional materials, early bonuses, special discounts, and join live events with the author.🔓 Pro Edition Bonus Pack (Early Access – $60) 🔥🔥🔥 Includes everything above, plus:✅ Premium Templates — plug-and-play workflows✅ Extended Case Studies — deep analyses across major industries✅ Cheat Sheets & Flashcards — quick-reference model guides and best practices✅ Behind-the-Scenes Notebooks — annotated walkthroughs and exploratory pipelines✅ Tabular Model Selection Toolkit — Python notebooks to benchmark, optimize, and compare📈 Ideal for professionals and teams who want to build and deploy faster—and sidestep the guesswork.✍️ About the AuthorWritten by Valeriy Manokhin, PhD, MBA, CQF — a seasoned forecasting expert, data scientist, and machine learning researcher with publications in top academic journals.Valeriy has advised both startups and large enterprises, helping them build and rebuild forecasting systems at scale. He has led successful forecasting initiatives for global organizations — including winning competitive tenders from multinational companies, outperforming major consulting firms like BCG and specialized AI startups focused on forecasting. He has delivered production-grade solutions for industry leaders such as Stanley Black & Decker and GfK.His methods have driven multimillion-dollar business impact, and his training programs have reached professionals in over 40 countries. This book is now used in more than 100+ countries and has become a #1-ranked title in Machine Learning, Forecasting, and Time Series across major platforms.🌍 Trusted By and Taught ToValeriy’s expertise is trusted by leaders at:Amazon, Apple, Google, Meta, Nike, BlackRock, Morgan Stanley, Target, NTT Data, Mars Inc., Lidl, Publicis Sapient, and more.His frameworks are followed by professionals from:University of Chicago, KTH (Sweden), UBC (Canada), DTU (Denmark), and other world-class institutions.👤 Students include:VPs of Engineering, AI Leads, Principal & Lead Data Scientists, ML Engineers, Consultants, Professors, Founders, Researchers, and PhD students.📚 Also by the AuthorMastering Modern Time Series ForecastingThe book trusted by data science leaders in 100+ countries. Unlock the toolkit behind today’s most powerful forecasting systems.Learn more → MasteringModernTimeSeriesForecasting⚡ Ready to Master the Best Tabular Model in ML?CatBoost isn’t just another gradient booster.It’s the most underappreciated breakthrough in machine learning—and you’re about to master it.👉 Grab your copy now and start building faster, better models with less tuning.

If you work with tabular data, this is your unfair advantage. Preorder now.

valeman.gumroad.com/...

#MachineLearning #DataScience #CatBoost #XGBoost #Kaggle #GradientBoosting #AI #MLEngineering #MasteringCatBoost

Valeriy M., PhD, MBA, CQF

@predict-addict.bsky.social

6 months ago

🚀 Mastering CatBoost: The Hidden Gem of Tabular AI (Early Release Preorder) 🛒 Pre‑Order Details Incremental chapter release: Chapters are released gradually. As content drops, both the value and price climb over time. Lifetime updates included: By preordering now, you’ll receive every current and future update for the book at no extra cost. By Valeriy Manokhin, PhD, MBA, CQF “CatBoost is not just underrated—it’s objectively better.”This book shows you why, with the science and the code to prove it. 💸 Pricing 🎉 Launch Price: $30 | Minimum: $25Will increase to $60+ as content grows. As the content continues to grow, if you find value in it—or simply want to support the project—you're welcome to contribute whatever it’s worth to you ❤️. 🧠 Why CatBoost?There’s a preponderance of scientific evidence that CatBoost consistently and significantly (20%+ according to TabArena outperforms XGBoost, and LightGBM on real-world tabular data.It's faster in inference, easier to tune, and built from the ground up for categorical features—without the usual preprocessing hacks.Despite this, CatBoost remains one of the most underused tools in machine learning. This book fixes that.🧪 Backed by research, benchmarks, and production experience📈 Practical, readable, hands-on for working data scientists🔬 Linked to the open-source repo: Awesome CatBoost🔍 What You’ll Learn Core architecture: how CatBoost works under the hood Hands-on modeling: end-to-end tabular ML pipelines Categorical encoding: no more label/one-hot hacks Overfitting detection: built-in, automated safeguards Evaluation strategies: cross-validation the CatBoost way Interpretability: SHAP, feature importance, monotonic constraints Bonus: Time series with CatBoost + quantile & uncertainty modeling 📘 Scope & Depth: More than Just Boosters Mastering CatBoost covers: Not just classification, but regression, ranking, time series, and even quantile/uncertainty models Deep dive into categorical feature handling (CatBoost’s core advantage) Native overfitting detection, monotonic constraints, and interpretability tools all built-in and tuned for tabular workflows 🏗️ Under-the-Hood Architecture & Scientific Advantages Harrison’s book provides intuition and tuning advice, with code examples and deployment workflows . Mastering CatBoost delves into: Ordered boosting, symmetric trees, and smoothed target statistics — explaining why CatBoost handles categorical variables without leakage Scientific benchmarks consistently show CatBoost outperforming XGBoost and LightGBM on real-world tabular datasets Includes newer capabilities like GPU optimizations, quantization, and ONNX export 🧩 Interpretability & Safeguards Native overfitting detection, eliminating guesswork Built-in per-feature importance, interaction, and partial dependence tools Monotonic constraints tuned specifically for CatBoost internals 🎯 The Verdict Mastering CatBoost goes far beyond: In technical depth (architecture + categorical handling) Applied scope (classification, regression, ranking, forecasting) Deployment readiness (quantization, ONNX, real-world pipelines) Support materials (Awesome_CatBoost repo, notebooks, domain-specific chapters) 👨‍💻 Who Is This For?This book is designed for: Machine learning engineers using tabular datasets Data scientists tired of endless hyperparameter tuning Students or researchers who’ve hit limits with XGBoost or sklearn Practitioners who want to move fast from data to insight If you like fast iteration, fewer bugs, and state-of-the-art tabular models, this book is for you.📦 What You Get📥 Instant access to the book — start reading immediately.🔄 Free updates — including new chapters, bug fixes, and bonus content.💬 Exclusive access to the private Discord community — connect with fellow readers, get additional materials, early bonuses, special discounts, and join live events with the author.🔓 Pro Edition Bonus Pack (Early Access – $60) 🔥🔥🔥 Includes everything above, plus:✅ Premium Templates — plug-and-play workflows✅ Extended Case Studies — deep analyses across major industries✅ Cheat Sheets & Flashcards — quick-reference model guides and best practices✅ Behind-the-Scenes Notebooks — annotated walkthroughs and exploratory pipelines✅ Tabular Model Selection Toolkit — Python notebooks to benchmark, optimize, and compare📈 Ideal for professionals and teams who want to build and deploy faster—and sidestep the guesswork.✍️ About the AuthorWritten by Valeriy Manokhin, PhD, MBA, CQF — a seasoned forecasting expert, data scientist, and machine learning researcher with publications in top academic journals.Valeriy has advised both startups and large enterprises, helping them build and rebuild forecasting systems at scale. He has led successful forecasting initiatives for global organizations — including winning competitive tenders from multinational companies, outperforming major consulting firms like BCG and specialized AI startups focused on forecasting. He has delivered production-grade solutions for industry leaders such as Stanley Black & Decker and GfK.His methods have driven multimillion-dollar business impact, and his training programs have reached professionals in over 40 countries. This book is now used in more than 100+ countries and has become a #1-ranked title in Machine Learning, Forecasting, and Time Series across major platforms.🌍 Trusted By and Taught ToValeriy’s expertise is trusted by leaders at:Amazon, Apple, Google, Meta, Nike, BlackRock, Morgan Stanley, Target, NTT Data, Mars Inc., Lidl, Publicis Sapient, and more.His frameworks are followed by professionals from:University of Chicago, KTH (Sweden), UBC (Canada), DTU (Denmark), and other world-class institutions.👤 Students include:VPs of Engineering, AI Leads, Principal & Lead Data Scientists, ML Engineers, Consultants, Professors, Founders, Researchers, and PhD students.📚 Also by the AuthorMastering Modern Time Series ForecastingThe book trusted by data science leaders in 100+ countries. Unlock the toolkit behind today’s most powerful forecasting systems.Learn more → MasteringModernTimeSeriesForecasting⚡ Ready to Master the Best Tabular Model in ML?CatBoost isn’t just another gradient booster.It’s the most underappreciated breakthrough in machine learning—and you’re about to master it.👉 Grab your copy now and start building faster, better models with less tuning.

XGBoost: After a decade… still basically pretending categorical features don’t exist.
📘 For the full deep dive, including how CatBoost leapfrogs XGBoost on categorical data, check out my book: Mastering CatBoost

valeman.gumroad.com/...

valeman.gumroad.com/...

#tabulardata #datascience #catboost

Valeriy M., PhD, MBA, CQF

@predict-addict.bsky.social

6 months ago

When you combine that with recent Kaggle wins like “CatBoost All The Way Down”, the shift in the competitive ML landscape becomes impossible to ignore.
#MachineLearning #CatBoost #Kaggle #AI #DataScience #MLBenchmarks

Valeriy M., PhD, MBA, CQF

@predict-addict.bsky.social

6 months ago

Whether you’re aiming to win Kaggle competitions, deploy robust models in production, or simply level up your ML toolkit, Mastering CatBoost will get you there.
#MachineLearning #DataScience #CatBoost #ML #AI #GradientBoosting #GBDT #Kaggle #Python #MLOps #TabularData #BookLaunch

Valeriy M., PhD, MBA, CQF

@predict-addict.bsky.social

6 months ago

More like laggard both in performance and innovation that has been coping new features from both CatBoost and LightGBM.

Despite XGBoost copycatting best features from CatBoost and LightGBM CatBoost retains the advantages due to mathematically better design.

#CatBoost

Valeriy M., PhD, MBA, CQF

@predict-addict.bsky.social

6 months ago

n independent testing by AutoML framework mljar, CatBoost trounces XGBoost across all tasks from binary to multiclass classification to regression.

mljar.com/machine-le...

#CatBoost #xgboost

Valeriy M., PhD, MBA, CQF

@predict-addict.bsky.social

6 months ago

🚀 Pro Edition → Book + Bonus Pack "Mastering CatBoost: The Hidden Gem of Tabular AI " (Early Release Preorder) 🔥 Pro Edition: "Mastering CatBoost: The Hidden Gem of Tabular AI" (Early Access) The elite version of the book — trusted by data science leaders in 100+ countries.Unlock the premium toolkit behind today’s most powerful model for tabular data. 🚀🚀🚀 New: Pro Edition Now Available — $60 (USD) 🔥🔥🔥Includes everything in the standard edition plus: premium templates, cheat sheets, extended case studies, behind‑the‑scenes notebooks, model tuning toolkits, and access to live Q&A + AMA sessions with the author.⚠️ Final price of Pro Edition will rise to $150+ at book completion. See 📦 What You Get and 💸 Pricing for full details. By Valeriy Manokhin, PhD, MBA, CQF “CatBoost is not just underrated—it’s objectively better.”This book shows you why, with the science and the code to prove it. 🔓 Pro Edition Bonus Pack (Early Access – $60) Includes everything above, plus: ✅ Premium Templates — plug-and-play workflows✅ Extended Case Studies — deep analyses across major industries✅ Cheat Sheets & Flashcards — quick-reference model guides and best practices✅ Behind-the-Scenes Notebooks — annotated walkthroughs and exploratory pipelines✅ Model Selection Toolkit — Python notebooks to benchmark, optimize, and compare 📈 Ideal for professionals and teams who want to build and deploy faster—and sidestep the guesswork. 💸 Pricing 🚀 Pro Edition Early Access: Price: $70 | Minimum: $60Includes the full book + Premium Pack.✅ Lock in now—price will rise to $150+ at full release. As the content continues to grow, if you find value in it—or simply want to support the project—you're welcome to contribute whatever it’s worth to you ❤️. Ready to take your tabular machine learning skills to next level? 👉 Hit Buy Now, and if you want structured support, check out the course at 🧠 Why CatBoost? There’s a preponderance of scientific evidence that CatBoost consistently and significantly (20%+ according to TabArena outperforms XGBoost, and LightGBM on real-world tabular data.It's faster in inference, easier to tune, and built from the ground up for categorical features—without the usual preprocessing hacks.Despite this, CatBoost remains one of the most underused tools in machine learning. This book fixes that.🧪 Backed by research, benchmarks, and production experience📈 Practical, readable, hands-on for working data scientists🔬 Linked to the open-source repo: Awesome CatBoost🔍 What You’ll Learn Core architecture: how CatBoost works under the hood Hands-on modeling: end-to-end tabular ML pipelines Categorical encoding: no more label/one-hot hacks Overfitting detection: built-in, automated safeguards Evaluation strategies: cross-validation the CatBoost way Interpretability: SHAP, feature importance, monotonic constraints Bonus: Time series with CatBoost + quantile & uncertainty modeling 📘 Scope & Depth: More than Just Boosters Mastering CatBoost covers: Not just classification, but regression, ranking, time series, and even quantile/uncertainty models Deep dive into categorical feature handling (CatBoost’s core advantage) Native overfitting detection, monotonic constraints, and interpretability tools all built-in and tuned for tabular workflows 🏗️ Under-the-Hood Architecture & Scientific Advantages Harrison’s book provides intuition and tuning advice, with code examples and deployment workflows . Mastering CatBoost delves into: Ordered boosting, symmetric trees, and smoothed target statistics — explaining why CatBoost handles categorical variables without leakage Scientific benchmarks consistently show CatBoost outperforming XGBoost and LightGBM on real-world tabular datasets Includes newer capabilities like GPU optimizations, quantization, and ONNX export 🧩 Interpretability & Safeguards Native overfitting detection, eliminating guesswork Built-in per-feature importance, interaction, and partial dependence tools Monotonic constraints tuned specifically for CatBoost internals 🎯 The Verdict Mastering CatBoost goes far beyond: In technical depth (architecture + categorical handling) Applied scope (classification, regression, ranking, forecasting) Deployment readiness (quantization, ONNX, real-world pipelines) Support materials (Awesome_CatBoost repo, notebooks, domain-specific chapters) 👨‍💻 Who Is This For?This book is designed for: Machine learning engineers using tabular datasets Data scientists tired of endless hyperparameter tuning Students or researchers who’ve hit limits with XGBoost or sklearn Practitioners who want to move fast from data to insight If you like fast iteration, fewer bugs, and state-of-the-art tabular models, this book is for you.📦 What You Get📥 Instant access to the book — start reading immediately.🔄 Free updates — including new chapters, bug fixes, and bonus content.💬 Exclusive access to the private Discord community — connect with fellow readers, get additional materials, early bonuses, special discounts, and join live events with the author.🔓 Pro Edition Bonus Pack (Early Access – $60) 🔥🔥🔥 Includes everything above, plus:✅ Premium Templates — plug-and-play workflows✅ Extended Case Studies — deep analyses across major industries✅ Cheat Sheets & Flashcards — quick-reference model guides and best practices✅ Behind-the-Scenes Notebooks — annotated walkthroughs and exploratory pipelines✅ Tabular Model Selection Toolkit — Python notebooks to benchmark, optimize, and compare📈 Ideal for professionals and teams who want to build and deploy faster—and sidestep the guesswork.✍️ About the AuthorWritten by Valeriy Manokhin, PhD, MBA, CQF — a seasoned forecasting expert, data scientist, and machine learning researcher with publications in top academic journals.Valeriy has advised both startups and large enterprises, helping them build and rebuild forecasting systems at scale. He has led successful forecasting initiatives for global organizations — including winning competitive tenders from multinational companies, outperforming major consulting firms like BCG and specialized AI startups focused on forecasting. He has delivered production-grade solutions for industry leaders such as Stanley Black & Decker and GfK.His methods have driven multimillion-dollar business impact, and his training programs have reached professionals in over 40 countries. This book is now used in more than 100+ countries and has become a #1-ranked title in Machine Learning, Forecasting, and Time Series across major platforms.🌍 Trusted By and Taught ToValeriy’s expertise is trusted by leaders at:Amazon, Apple, Google, Meta, Nike, BlackRock, Morgan Stanley, Target, NTT Data, Mars Inc., Lidl, Publicis Sapient, and more.His frameworks are followed by professionals from:University of Chicago, KTH (Sweden), UBC (Canada), DTU (Denmark), and other world-class institutions.👤 Students include:VPs of Engineering, AI Leads, Principal & Lead Data Scientists, ML Engineers, Consultants, Professors, Founders, Researchers, and PhD students.📚 Also by the AuthorMastering Modern Time Series ForecastingThe book trusted by data science leaders in 100+ countries. Unlock the toolkit behind today’s most powerful forecasting systems.Learn more → MasteringModernTimeSeriesForecasting⚡ Ready to Master the Best Tabular Model in ML?CatBoost isn’t just another gradient booster.It’s the most underappreciated breakthrough in machine learning—and you’re about to master it.👉 Grab your copy now and start building faster, better models with less tuning.

#catboost

Mastering CatBoost -> valeman.gumroad.com/...

Pro ->

Valeriy M., PhD, MBA, CQF

@predict-addict.bsky.social

6 months ago

Unlike CatBoost and LightGBM, XGBoost could not even handle categorical features properly.

And then it just copied the idea from CatBoost and XGBoost.

When something is a copycat it is a laggard and follower, not innovator.

#CatBoost #xgboost

Valeriy M., PhD, MBA, CQF

@predict-addict.bsky.social

6 months ago

Meanwhile, CatBoost was built by a handful of people at Yandex and just… works.

#xgboost #catboost

Valeriy M., PhD, MBA, CQF

@predict-addict.bsky.social

6 months ago

In practice, many datasets include such features, but there was bad support for such types of predictors in open-source libraries, and CatBoost fills the gap: CatBoost was compared with with XGBoost, LightGBM and H2O and outperforms competitors on several publicly available dataset.

#catboost

Valeriy M., PhD, MBA, CQF

@predict-addict.bsky.social

6 months ago

* CatBoost achieves the best average rank in most classification and regression tasks, which is consistent with previous studies.

* Among all deep tabular methods, TabR works the best in most cases. However, it has a high training cost

#catboost
#tabulardata
#deeplearning

Valeriy M., PhD, MBA, CQF

@predict-addict.bsky.social

7 months ago

Consequently, estimating the total training time becomes a straightforward mathematical calculation, enhancing the user's planning and management of the model training process.

#catboost

Valeriy M., PhD, MBA, CQF

@predict-addict.bsky.social

7 months ago

🚀 Mastering CatBoost: The Hidden Gem of Tabular AI (Early Release Preorder) 🛒 Pre‑Order Details Incremental chapter release: Chapters are released gradually. As content drops, both the value and price climb over time. Lifetime updates included: By preordering now, you’ll receive every current and future update for the book at no extra cost. By Valeriy Manokhin, PhD, MBA, CQF “CatBoost is not just underrated—it’s objectively better.”This book shows you why, with the science and the code to prove it. 💸 Pricing 🎉 Launch Price: $30 | Minimum: $25Will increase to $60+ as content grows. As the content continues to grow, if you find value in it—or simply want to support the project—you're welcome to contribute whatever it’s worth to you ❤️. 🧠 Why CatBoost?There’s a preponderance of scientific evidence that CatBoost consistently and significantly (20%+ according to TabArena outperforms XGBoost, and LightGBM on real-world tabular data.It's faster in inference, easier to tune, and built from the ground up for categorical features—without the usual preprocessing hacks.Despite this, CatBoost remains one of the most underused tools in machine learning. This book fixes that.🧪 Backed by research, benchmarks, and production experience📈 Practical, readable, hands-on for working data scientists🔬 Linked to the open-source repo: Awesome CatBoost🔍 What You’ll Learn Core architecture: how CatBoost works under the hood Hands-on modeling: end-to-end tabular ML pipelines Categorical encoding: no more label/one-hot hacks Overfitting detection: built-in, automated safeguards Evaluation strategies: cross-validation the CatBoost way Interpretability: SHAP, feature importance, monotonic constraints Bonus: Time series with CatBoost + quantile & uncertainty modeling 📘 Scope & Depth: More than Just Boosters Mastering CatBoost covers: Not just classification, but regression, ranking, time series, and even quantile/uncertainty models Deep dive into categorical feature handling (CatBoost’s core advantage) Native overfitting detection, monotonic constraints, and interpretability tools all built-in and tuned for tabular workflows 🏗️ Under-the-Hood Architecture & Scientific Advantages Harrison’s book provides intuition and tuning advice, with code examples and deployment workflows . Mastering CatBoost delves into: Ordered boosting, symmetric trees, and smoothed target statistics — explaining why CatBoost handles categorical variables without leakage Scientific benchmarks consistently show CatBoost outperforming XGBoost and LightGBM on real-world tabular datasets Includes newer capabilities like GPU optimizations, quantization, and ONNX export 🧩 Interpretability & Safeguards Native overfitting detection, eliminating guesswork Built-in per-feature importance, interaction, and partial dependence tools Monotonic constraints tuned specifically for CatBoost internals 🎯 The Verdict Mastering CatBoost goes far beyond: In technical depth (architecture + categorical handling) Applied scope (classification, regression, ranking, forecasting) Deployment readiness (quantization, ONNX, real-world pipelines) Support materials (Awesome_CatBoost repo, notebooks, domain-specific chapters) 👨‍💻 Who Is This For?This book is designed for: Machine learning engineers using tabular datasets Data scientists tired of endless hyperparameter tuning Students or researchers who’ve hit limits with XGBoost or sklearn Practitioners who want to move fast from data to insight If you like fast iteration, fewer bugs, and state-of-the-art tabular models, this book is for you.📦 What You Get📥 Instant access to the book — start reading immediately.🔄 Free updates — including new chapters, bug fixes, and bonus content.💬 Exclusive access to the private Discord community — connect with fellow readers, get additional materials, early bonuses, special discounts, and join live events with the author.🔓 Pro Edition Bonus Pack (Early Access – $60) 🔥🔥🔥 Includes everything above, plus:✅ Premium Templates — plug-and-play workflows✅ Extended Case Studies — deep analyses across major industries✅ Cheat Sheets & Flashcards — quick-reference model guides and best practices✅ Behind-the-Scenes Notebooks — annotated walkthroughs and exploratory pipelines✅ Tabular Model Selection Toolkit — Python notebooks to benchmark, optimize, and compare📈 Ideal for professionals and teams who want to build and deploy faster—and sidestep the guesswork.✍️ About the AuthorWritten by Valeriy Manokhin, PhD, MBA, CQF — a seasoned forecasting expert, data scientist, and machine learning researcher with publications in top academic journals.Valeriy has advised both startups and large enterprises, helping them build and rebuild forecasting systems at scale. He has led successful forecasting initiatives for global organizations — including winning competitive tenders from multinational companies, outperforming major consulting firms like BCG and specialized AI startups focused on forecasting. He has delivered production-grade solutions for industry leaders such as Stanley Black & Decker and GfK.His methods have driven multimillion-dollar business impact, and his training programs have reached professionals in over 40 countries. This book is now used in more than 100+ countries and has become a #1-ranked title in Machine Learning, Forecasting, and Time Series across major platforms.🌍 Trusted By and Taught ToValeriy’s expertise is trusted by leaders at:Amazon, Apple, Google, Meta, Nike, BlackRock, Morgan Stanley, Target, NTT Data, Mars Inc., Lidl, Publicis Sapient, and more.His frameworks are followed by professionals from:University of Chicago, KTH (Sweden), UBC (Canada), DTU (Denmark), and other world-class institutions.👤 Students include:VPs of Engineering, AI Leads, Principal & Lead Data Scientists, ML Engineers, Consultants, Professors, Founders, Researchers, and PhD students.📚 Also by the AuthorMastering Modern Time Series ForecastingThe book trusted by data science leaders in 100+ countries. Unlock the toolkit behind today’s most powerful forecasting systems.Learn more → MasteringModernTimeSeriesForecasting⚡ Ready to Master the Best Tabular Model in ML?CatBoost isn’t just another gradient booster.It’s the most underappreciated breakthrough in machine learning—and you’re about to master it.👉 Grab your copy now and start building faster, better models with less tuning.

If you work with tabular data, this is your unfair advantage. Preorder now.

valeman.gumroad.com/...

#MachineLearning #DataScience #CatBoost #XGBoost #Kaggle #GradientBoosting #AI #MLEngineering #MasteringCatBoost

Valeriy M., PhD, MBA, CQF

@predict-addict.bsky.social

7 months ago

Whether you’re aiming to win Kaggle competitions, deploy robust models in production, or simply level up your ML toolkit, Mastering CatBoost will get you there.
#MachineLearning #DataScience #CatBoost #ML #AI #GradientBoosting #GBDT #Kaggle #Python #MLOps #TabularData #BookLaunch

Valeriy M., PhD, MBA, CQF

@predict-addict.bsky.social

7 months ago

🚀 Mastering CatBoost: The Hidden Gem of Tabular AI (Early Release Preorder) 🛒 Pre‑Order Details Incremental chapter release: Chapters are released gradually. As content drops, both the value and price climb over time. Lifetime updates included: By preordering now, you’ll receive every current and future update for the book at no extra cost. By Valeriy Manokhin, PhD, MBA, CQF “CatBoost is not just underrated—it’s objectively better.”This book shows you why, with the science and the code to prove it. 💸 Pricing 🎉 Launch Price: $30 | Minimum: $25Will increase to $60+ as content grows. As the content continues to grow, if you find value in it—or simply want to support the project—you're welcome to contribute whatever it’s worth to you ❤️. 🧠 Why CatBoost?There’s a preponderance of scientific evidence that CatBoost consistently and significantly (20%+ according to TabArena outperforms XGBoost, and LightGBM on real-world tabular data.It's faster in inference, easier to tune, and built from the ground up for categorical features—without the usual preprocessing hacks.Despite this, CatBoost remains one of the most underused tools in machine learning. This book fixes that.🧪 Backed by research, benchmarks, and production experience📈 Practical, readable, hands-on for working data scientists🔬 Linked to the open-source repo: Awesome CatBoost🔍 What You’ll Learn Core architecture: how CatBoost works under the hood Hands-on modeling: end-to-end tabular ML pipelines Categorical encoding: no more label/one-hot hacks Overfitting detection: built-in, automated safeguards Evaluation strategies: cross-validation the CatBoost way Interpretability: SHAP, feature importance, monotonic constraints Bonus: Time series with CatBoost + quantile & uncertainty modeling 📘 Scope & Depth: More than Just Boosters Mastering CatBoost covers: Not just classification, but regression, ranking, time series, and even quantile/uncertainty models Deep dive into categorical feature handling (CatBoost’s core advantage) Native overfitting detection, monotonic constraints, and interpretability tools all built-in and tuned for tabular workflows 🏗️ Under-the-Hood Architecture & Scientific Advantages Harrison’s book provides intuition and tuning advice, with code examples and deployment workflows . Mastering CatBoost delves into: Ordered boosting, symmetric trees, and smoothed target statistics — explaining why CatBoost handles categorical variables without leakage Scientific benchmarks consistently show CatBoost outperforming XGBoost and LightGBM on real-world tabular datasets Includes newer capabilities like GPU optimizations, quantization, and ONNX export 🧩 Interpretability & Safeguards Native overfitting detection, eliminating guesswork Built-in per-feature importance, interaction, and partial dependence tools Monotonic constraints tuned specifically for CatBoost internals 🎯 The Verdict Mastering CatBoost goes far beyond: In technical depth (architecture + categorical handling) Applied scope (classification, regression, ranking, forecasting) Deployment readiness (quantization, ONNX, real-world pipelines) Support materials (Awesome_CatBoost repo, notebooks, domain-specific chapters) 👨‍💻 Who Is This For?This book is designed for: Machine learning engineers using tabular datasets Data scientists tired of endless hyperparameter tuning Students or researchers who’ve hit limits with XGBoost or sklearn Practitioners who want to move fast from data to insight If you like fast iteration, fewer bugs, and state-of-the-art tabular models, this book is for you.📦 What You Get📥 Instant access to the book — start reading immediately.🔄 Free updates — including new chapters, bug fixes, and bonus content.💬 Exclusive access to the private Discord community — connect with fellow readers, get additional materials, early bonuses, special discounts, and join live events with the author.🔓 Pro Edition Bonus Pack (Early Access – $60) 🔥🔥🔥 Includes everything above, plus:✅ Premium Templates — plug-and-play workflows✅ Extended Case Studies — deep analyses across major industries✅ Cheat Sheets & Flashcards — quick-reference model guides and best practices✅ Behind-the-Scenes Notebooks — annotated walkthroughs and exploratory pipelines✅ Tabular Model Selection Toolkit — Python notebooks to benchmark, optimize, and compare📈 Ideal for professionals and teams who want to build and deploy faster—and sidestep the guesswork.✍️ About the AuthorWritten by Valeriy Manokhin, PhD, MBA, CQF — a seasoned forecasting expert, data scientist, and machine learning researcher with publications in top academic journals.Valeriy has advised both startups and large enterprises, helping them build and rebuild forecasting systems at scale. He has led successful forecasting initiatives for global organizations — including winning competitive tenders from multinational companies, outperforming major consulting firms like BCG and specialized AI startups focused on forecasting. He has delivered production-grade solutions for industry leaders such as Stanley Black & Decker and GfK.His methods have driven multimillion-dollar business impact, and his training programs have reached professionals in over 40 countries. This book is now used in more than 100+ countries and has become a #1-ranked title in Machine Learning, Forecasting, and Time Series across major platforms.🌍 Trusted By and Taught ToValeriy’s expertise is trusted by leaders at:Amazon, Apple, Google, Meta, Nike, BlackRock, Morgan Stanley, Target, NTT Data, Mars Inc., Lidl, Publicis Sapient, and more.His frameworks are followed by professionals from:University of Chicago, KTH (Sweden), UBC (Canada), DTU (Denmark), and other world-class institutions.👤 Students include:VPs of Engineering, AI Leads, Principal & Lead Data Scientists, ML Engineers, Consultants, Professors, Founders, Researchers, and PhD students.📚 Also by the AuthorMastering Modern Time Series ForecastingThe book trusted by data science leaders in 100+ countries. Unlock the toolkit behind today’s most powerful forecasting systems.Learn more → MasteringModernTimeSeriesForecasting⚡ Ready to Master the Best Tabular Model in ML?CatBoost isn’t just another gradient booster.It’s the most underappreciated breakthrough in machine learning—and you’re about to master it.👉 Grab your copy now and start building faster, better models with less tuning.

But don’t worry, XGBoost enthusiasts—I am compiling everything you need to get started in the Mastering CatBoost book.

valeman.gumroad.com/...

Get Pro -> valeman.gumroad.com/...

#CatBoost

#xgboost