b/learning-path by booms

Python Machine Learning Cookbook: Practical solutions from preprocessing to deep learning [Early Release]

This post was published 8 years ago. Download links are most likely obsolete. If that's the case, try asking the uploader to re-upload.

Python Machine Learning Cookbook: Practical solutions from preprocessing to deep learning

170 pages | Oct 2017 | English | ISBN-10: 1491989386 | PDF | 1.5 MB

The Python programming language and its libraries, including pandas and scikit-learn, provide a production-grade environment to help you accomplish a broad range of machine-learning tasks. With this comprehensive cookbook, data scientists and software engineers familiar with Python will benefit from almost 200 practical recipes for building a comprehensive machine-learning pipeline—everything from data preprocessing and feature engineering to model evaluation and deep learning.

Learn from author Chris Albon, a data scientist who has written more than 500 tutorials on Python, data science, and machine learning. Each recipe in this practical cookbook includes code solutions that you can put to work right away, along with a discussion of how and why they work—making it ideal as a learning tool and reference book.