Mastering Feature Engineering Principles and Techniques for Data Scientists (Early Release)

Feature Engineering for Machine Learning

📁 Feature Engineering for Machine Learning: Principles and Techniques for Data Scientists

✍ Alice Zheng, Amanda Casari 📂 Library 📅 2018 🏛 O’Reilly Media 🌐 English

Feature engineering is a crucial step in the machine-learning pipeline, yet this topic is rarely examined on its own. With this practical book, you’ll learn techniques for extracting and transforming features—the numeric representations of raw data—into formats for machine-learning models. Each chap

Feature Engineering for Machine Learning

📁 Feature Engineering for Machine Learning: Principles and Techniques for Data Scientists

✍ Alice Zheng, Amanda Casari 📂 Library 📅 2018 🏛 O’Reilly Media 🌐 English

Feature engineering is a crucial step in the machine-learning pipeline, yet this topic is rarely examined on its own. With this practical book, you’ll learn techniques for extracting and transforming features—the numeric representations of raw data—into formats for machine-learning models. Each chap

Feature engineering for machine learning

📁 Feature engineering for machine learning: principles and techniques for data scientists

✍ Casari, Amanda;Zheng, Alice 📂 Library 📅 2018 🏛 O'Reilly Media, Inc. 🌐 English

Intro; Copyright; Table of Contents; Preface; Introduction; Conventions Used in This Book; Using Code Examples; O'Reilly Safari; How to Contact Us; Acknowledgments; Special Thanks from Alice; Special Thanks from Amanda; Chapter 1. The Machine Learning Pipeline; Data; Tasks; Models; Features; Model E

Software Engineering for Data Scientists

📁 Software Engineering for Data Scientists (Early Release)

✍ Catherine Nelson 📂 Library 📅 2024 🏛 O'Reilly Media, Inc. 🌐 English

Data science happens in code. The ability to write reproducible, robust, scaleable code is key to a data science project's success—and is absolutely essential for those working with production code. This practical book bridges the gap between data science and software engineering, clearly explaining

Mathematical Techniques for Engineers an

📁 Mathematical Techniques for Engineers and Scientists

✍ Larry C. Andrews, Ronald L. Phillips 📂 Library 📅 2003 🏛 SPIE Publications 🌐 English

As technology continues to move ahead, modern engineers and scientists are frequently faced with difficult mathematical problems that require an ever greater understanding of advanced concepts. Designed as a self-study text for practicing engineers and scientists, as well as a useful reference, the

Engineering of Additive Manufacturing Fe

📁 Engineering of Additive Manufacturing Features for Data-Driven Solutions: Sources, Techniques, Pipelines, and Applications

✍ Mutahar Safdar, Guy Lamouche, Padma Polash Paul, Gentry Wood, Yaoyao Fiona Zhao 📂 Library 📅 2023 🏛 Springer 🌐 English

<p><span>This book is a comprehensive guide to the latest developments in data-driven additive manufacturing (AM). From data mining and pre-processing to signal processing, computer vision, and more, the book covers all the essential techniques for preparing AM data. Readers willl explore the key ph