Author(s) Name:  Henrik Brink Joseph W. Richards Mark Fetherolf
Real-World Machine Learning is a practical guide designed to teach working developers the art of ML project execution. Without overdosing you on academic theory and complex mathematics, it introduces the day-to-day practice of machine learning, preparing you to successfully build and deploy powerful ML systems.
Table of Contents
Part 1. The machine-learning workflow
Chapter 1. What is machine learning?
Chapter 2. Real-world data
Chapter 3. Modeling and prediction
Chapter 4. Model evaluation and optimization
Chapter 5. Basic feature engineering
Part 2. Practical application
Chapter 6. Example: NYC taxi data
Chapter 7. Advanced feature engineering
Chapter 8. Advanced NLP example: movie review sentiment
Chapter 9. Scaling machine-learning workflows
Chapter 10. Example: digital display advertising
ISBN:  9781617291920
Publisher:  Manning Publications
Year of Publication:  2016
Book Link:  Home Page Url