Python for Advanced Machine Learning: From Feature Engineering to Scalable AI Models
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- FormatePub
- ISBN8227792938
- EAN9798227792938
- Date de parution01/05/2025
- Protection num.pas de protection
- Infos supplémentairesepub
- ÉditeurBig Dog Books, LLC
Résumé
Are you a data scientist striving to elevate your models beyond accuracy plateaus?Do you want to master feature engineering across numerical, textual, time-series, and image data?Are you looking for a complete, scalable, and production-ready approach to building intelligent AI pipelines?If you answered …
Are you a data scientist striving to elevate your models beyond accuracy plateaus?Do you want to master feature engineering across numerical, textual, time-series, and image data?Are you looking for a complete, scalable, and production-ready approach to building intelligent AI pipelines?If you answered YES to at least one of these questions, you MUST KEEP READING.Build better models, faster and smarter-transform your AI projects with advanced feature engineering and real-world pipeline designIn the evolving world of artificial intelligence, simply training models isn't enough.
Many machine learning practitioners struggle with underperforming models, unreliable predictions, and pipelines that can't scale. The problem? They underestimate the power of engineered features. Without strong foundations in preprocessing, data transformation, and domain-specific feature engineering, even the most sophisticated algorithms fail to deliver. But you're not alone in this journey.This book is your practical guide to mastering advanced machine learning through a unique, hands-on approachCrafted for experienced practitioners and aspiring AI experts, this book delivers a comprehensive methodology for building superior machine learning systems.
You'll uncover cutting-edge techniques in feature engineering, deep learning-based extractions, and real-world deployment strategies. Whether you work with text, images, time-series, or tabular data, this resource shows you how to create features that drive real impact. Backed by years of industry experience and research, this book introduces a unique method that brings together automation, fairness, and scalability-all in one.
What you'll discover inside: Data Preprocessing Mastery: How to handle missing values, detect outliers, and scale your data effectively High-Impact Feature Engineering: Strategies to extract, encode, and transform features for maximum model performance Domain-Specific Approaches: Best practices for engineering features from text, images, and time-series data Feature Selection Methods: Implement filter, wrapper, and embedded techniques to isolate the most predictive variables Production-Ready Pipelines: Build scalable systems, handle feature drift, and automate engineering in real-time ML applications And much more.
Imagine deploying machine learning models that are more accurate, more explainable, and ready for production-across any domain or data typeWith the knowledge in this book, you'll confidently handle complex data, create scalable pipelines, and transform your models into reliable, high-performing solutions. Unlock the full potential of Python and feature engineering-your AI projects will never be the same.
Get your copy now and take your machine learning skills to an expert level!
Many machine learning practitioners struggle with underperforming models, unreliable predictions, and pipelines that can't scale. The problem? They underestimate the power of engineered features. Without strong foundations in preprocessing, data transformation, and domain-specific feature engineering, even the most sophisticated algorithms fail to deliver. But you're not alone in this journey.This book is your practical guide to mastering advanced machine learning through a unique, hands-on approachCrafted for experienced practitioners and aspiring AI experts, this book delivers a comprehensive methodology for building superior machine learning systems.
You'll uncover cutting-edge techniques in feature engineering, deep learning-based extractions, and real-world deployment strategies. Whether you work with text, images, time-series, or tabular data, this resource shows you how to create features that drive real impact. Backed by years of industry experience and research, this book introduces a unique method that brings together automation, fairness, and scalability-all in one.
What you'll discover inside: Data Preprocessing Mastery: How to handle missing values, detect outliers, and scale your data effectively High-Impact Feature Engineering: Strategies to extract, encode, and transform features for maximum model performance Domain-Specific Approaches: Best practices for engineering features from text, images, and time-series data Feature Selection Methods: Implement filter, wrapper, and embedded techniques to isolate the most predictive variables Production-Ready Pipelines: Build scalable systems, handle feature drift, and automate engineering in real-time ML applications And much more.
Imagine deploying machine learning models that are more accurate, more explainable, and ready for production-across any domain or data typeWith the knowledge in this book, you'll confidently handle complex data, create scalable pipelines, and transform your models into reliable, high-performing solutions. Unlock the full potential of Python and feature engineering-your AI projects will never be the same.
Get your copy now and take your machine learning skills to an expert level!