Machine Learning with Python for Everyone (Addison-Wesley Data & Analytics Series) 1st Edition eTextbook by Mark E. Fenner

Complete eTextbook Content:
Part I: First Steps
Chapter 1: Let’s Discuss Learning
Chapter 2: Some Technical Background
Chapter 3: Predicting Categories: Getting Started with Classification
Chapter 4: Predicting Numerical Values: Getting Started with Regression
Part II: Evaluation
Chapter 5: Evaluating and Comparing Learners
Chapter 6: Evaluating Classifiers
Chapter 7: Evaluating Regressors
Part III: More Methods and Fundamentals
Chapter 8: More Classification Methods
Chapter 9: More Regression Methods
Chapter 10: Manual Feature Engineering: Manipulating Data for Fun and Profit
Chapter 11: Tuning Hyperparameters and Pipelines
Part IV: Adding Complexity
Chapter 12: Combining Learners
Chapter 13: Models That Engineer Features for Us
Chapter 14: Feature Engineering for Domains: Domain-Specific Learning
Chapter 15: Connections, Extensions, and Further Directions
Appendix A: mlwpy.py Listing

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Name: Machine Learning with Python for Everyone (Addison-Wesley Data & Analytics Series)
Author: Mark E. Fenner
Edition: 1st
ISBN-10: 0134845625
ISBN-13: 978-0134845623
Type: eTextbook

This is a eBook for the actual textbook of Machine Learning with Python for Everyone (Addison-Wesley Data & Analytics Series), by Mark E. Fenner.

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