Description
Details
Are you a data scientist looking to take your machine learning skills to the next level? Introducing "Feature Engineering for Machine Learning: Principles and Techniques for Data Scientists" - the ultimate guide to mastering feature engineering. This practical book teaches you how to extract and transform numeric representations of raw data into formats that are perfect for machine-learning models. Don't waste your time on outdated techniques - learn the latest and most effective methods for feature engineering.
With "Feature Engineering for Machine Learning," you'll gain invaluable knowledge and skills that will set you apart from the competition. Each chapter focuses on a specific data problem and provides step-by-step guidance on how to tackle it. From representing text and image data to handling categorical variables, this book covers it all. And with exercises throughout, you'll have plenty of opportunities to practice and reinforce what you've learned.
Unlike other books on the subject, "Feature Engineering for Machine Learning" doesn't stop at theory. The authors, Alice Zheng and Amanda Casari, prioritize practical application, ensuring that you can immediately implement what you've learned. The closing chapter dives into a real-world dataset, demonstrating how to apply various feature-engineering techniques and showcasing their impact on model performance.
When it comes to coding examples, "Feature Engineering for Machine Learning" uses popular Python packages like numpy, Pandas, Scikit-learn, and Matplotlib. This means you'll be able to put your new knowledge into practice using tools that are widely used in the industry. Don't miss this opportunity to level up your feature engineering skills - get your copy of "Feature Engineering for Machine Learning: Principles and Techniques for Data Scientists" now.
Ready to transform your machine learning projects with cutting-edge feature engineering techniques? Don't delay - get your hands on "Feature Engineering for Machine Learning: Principles and Techniques for Data Scientists" today and unlock the secrets to building more accurate and powerful machine-learning models.
Discover More Best Sellers in Databases & Big Data
Shop Databases & Big Data
Databases & Big Data - Developing High-Frequency Trading Systems: Learn how to implement high-frequency trading from scratch with C++ or Java basics
Building Real-Time Analytics Systems: From Events to Insights with Apache Kafka and Apache Pinot
Databases & Big Data - Building Real-Time Analytics Systems: From Events to Insights with Apache Kafka and Apache Pinot
Databases & Big Data - Storytelling with Charts: A Data & Text Visualization Guide for Business, Professionals and Non-Professionals: A tutorial to quickly master the art and science of telling engaging stories with charts
SQL in 10 Minutes a Day, Sams Teach Yourself
Databases & Big Data - SQL in 10 Minutes a Day, Sams Teach Yourself
Super Founders: What Data Reveals About Billion-Dollar Startups
Databases & Big Data - Super Founders: What Data Reveals About Billion-Dollar Startups
Databases & Big Data - Bundle: Illustrated Microsoft Office 365 & Office 2019 Introductory, Loose-leaf Version + MindTap, 1 term Printed Access Card
Electronic Value Exchange: Origins of the VISA Electronic Payment System (History of Computing)
Databases & Big Data - Electronic Value Exchange: Origins of the VISA Electronic Payment System (History of Computing)
The Self-Taught Computer Scientist: The Beginner's Guide to Data Structures & Algorithms
Databases & Big Data - The Self-Taught Computer Scientist: The Beginner's Guide to Data Structures & Algorithms


