Machine Learning with Python Cookbook, 2nd Edition (Full Colour Edition)

This book is a practical guide to solving machine learning problems with Python. It offers more than 200 self-contained recipes for challenges that can come up in real work, from loading data to training models and using neural networks. Each recipe has code to copy, paste and run on a toy dataset, followed by a discussion that explains the solution. Kyle Gallatin and Chris Albon wrote it for readers who already know Python, pandas and scikit-learn.

Why You Should Read?

• Find more than 200 self-contained recipes that each target a specific machine learning problem you may meet at work.
• Run the code in every recipe on a toy dataset to check that it works first.
• Adapt each tested recipe to your own use case or application once you have seen it run.
• Understand why each solution works through a discussion that gives meaningful context, going beyond theory and concepts.