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Feature Engineering for Modern Machine Learning with Scikit-Learn: Advanced Data Science and Practical Applications
This Book grants Free Access to our e-learning Platform, which ✅ Free Repository Code with all code blocks used in this book
✅ Access to Free Chapters of all our library of programming published books
✅ Free premium customer support
✅ Much more...
Unleash the Power of Feature Engineering for Cutting-Edge Machine LearningTransform raw data into powerful features with Feature Engineering for Modern Machine Learning with Advanced Data Science and Practical Applications. This essential guide takes you beyond the basics, teaching you how to create, optimize, and automate features that elevate machine learning models. With a focus on real-world applications and advanced techniques, this book equips data scientists, machine learning engineers, and analytics professionals with the skills to make impactful, data-driven decisions.
Why Advanced Feature Engineering is EssentialIn machine learning, the quality of input data determines the quality of output predictions. Advanced feature engineering is the key to uncovering hidden patterns and meaningful insights in your data, transforming it into structured inputs that drive model performance. This book provides a deep dive into creating and refining features tailored to your data’s unique challenges, ensuring models are both accurate and insightful.
What You’ll Discover InsideFeature Engineering for Modern Machine Learning with Scikit-Learn covers every stage of advanced feature engineering, from foundational transformations to automated pipelines and cutting-edge
Automating Data Preparation with Scikit-Learn Pipelines: Learn to create reproducible, automated workflows that handle everything from scaling and encoding to feature selection.Advanced Feature Creation and Transformation: Master complex techniques like polynomial features, interaction terms, and dimensionality reduction, all designed to improve model accuracy.Industry-Specific Case Studies: Apply feature engineering techniques to real-world domains like healthcare, retail, and customer segmentation, gaining insights into how feature engineering adapts across fields.Modern Tools and Automation with AutoML: Explore AutoML tools like TPOT and Auto-sklearn to automate feature selection and model optimization, allowing you to focus on the highest-impact features.Deep Learning Feature Engineering: Discover techniques tailored for neural networks, including data augmentation, embeddings, and feature transformations that enhance deep learning workflows.
Who Should Read This BookWhether you’re an experienced data scientist or an advanced beginner looking to build cutting-edge skills, this book provides essential techniques for modern machine learning. It’s ideal for anyone who wants
Maximize model performance through impactful feature engineering.Build efficient, reproducible workflows with Scikit-Learn.Explore advanced applications across multiple domains.
Elevate Your Models with Advanced Feature EngineeringFeature Engineering for Modern Machine Learning with Scikit-Learn is more than just a guide—it’s a toolkit for creating the data transformations that drive high-performing models.
✅ Access to Free Chapters of all our library of programming published books
✅ Free premium customer support
✅ Much more...
Unleash the Power of Feature Engineering for Cutting-Edge Machine LearningTransform raw data into powerful features with Feature Engineering for Modern Machine Learning with Advanced Data Science and Practical Applications. This essential guide takes you beyond the basics, teaching you how to create, optimize, and automate features that elevate machine learning models. With a focus on real-world applications and advanced techniques, this book equips data scientists, machine learning engineers, and analytics professionals with the skills to make impactful, data-driven decisions.
Why Advanced Feature Engineering is EssentialIn machine learning, the quality of input data determines the quality of output predictions. Advanced feature engineering is the key to uncovering hidden patterns and meaningful insights in your data, transforming it into structured inputs that drive model performance. This book provides a deep dive into creating and refining features tailored to your data’s unique challenges, ensuring models are both accurate and insightful.
What You’ll Discover InsideFeature Engineering for Modern Machine Learning with Scikit-Learn covers every stage of advanced feature engineering, from foundational transformations to automated pipelines and cutting-edge
Automating Data Preparation with Scikit-Learn Pipelines: Learn to create reproducible, automated workflows that handle everything from scaling and encoding to feature selection.Advanced Feature Creation and Transformation: Master complex techniques like polynomial features, interaction terms, and dimensionality reduction, all designed to improve model accuracy.Industry-Specific Case Studies: Apply feature engineering techniques to real-world domains like healthcare, retail, and customer segmentation, gaining insights into how feature engineering adapts across fields.Modern Tools and Automation with AutoML: Explore AutoML tools like TPOT and Auto-sklearn to automate feature selection and model optimization, allowing you to focus on the highest-impact features.Deep Learning Feature Engineering: Discover techniques tailored for neural networks, including data augmentation, embeddings, and feature transformations that enhance deep learning workflows.
Who Should Read This BookWhether you’re an experienced data scientist or an advanced beginner looking to build cutting-edge skills, this book provides essential techniques for modern machine learning. It’s ideal for anyone who wants
Maximize model performance through impactful feature engineering.Build efficient, reproducible workflows with Scikit-Learn.Explore advanced applications across multiple domains.
Elevate Your Models with Advanced Feature EngineeringFeature Engineering for Modern Machine Learning with Scikit-Learn is more than just a guide—it’s a toolkit for creating the data transformations that drive high-performing models.
700 pages, Kindle Edition
Published November 5, 2024
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2 people want to read
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Displaying 1 - 2 of 2 reviews
July 24, 2025
This book, "Feature Engineering for Modern Machine Learning with Scikit-Learn", goes way beyond the beginner stuff of ML. It dives deep with Scikit-Learn into creating powerful features using advanced techniques, even automating some of the grunt work with pipelines and AutoML. It has real-world case studies from different industries, and I was very glad for the e-learning platform access (can't beat free code!). Not for everyone, obviously, but it’s a proper practitioner's toolkit for anyone serious about making their ML models actually deliver impactful insights. I'll be using this for reference quite a lot.
May 25, 2025
Written by a team, read by no one. No input data, no output of code and no visualizations of all the plots the scripts create. This may work as a handout to a course or a video, but it does not work as a book.
Displaying 1 - 2 of 2 reviews