
Sách keo gáy, Bìa mềm
Thể loại:Computers - Databases
Năm:2018
Ngôn ngữ:english
Trang:218 / 217
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 chapter guides you through a single data problem, such as
how to represent text or image data. Together, these examples illustrate
the main principles of feature engineering.
Rather than simply teach
these principles, authors Alice Zheng and Amanda Casari focus on
practical application with exercises throughout the book. The closing
chapter brings everything together by tackling a real-world, structured
dataset with several feature-engineering techniques. Python packages
including numpy, Pandas, Scikit-learn, and Matplotlib are used in code
examples.