A Hands-On Introduction to Machine Learning

ISBN-13: 9781009123303 / Angielski / Twarda / 2022 / 500 str.

Chirag (University of Washington) Shah

Opis

A self-contained and practical introduction that assumes no prior knowledge of programming or machine learning.

Recenzje

'… an approachable exposition of machine learning with theories and context based on real-life, practical applications. Professor Shah interweaves theoretical concepts, such as dimensionality reduction, gradient descent, and reinforcement learning, with hands-on examples that are easy to understand. This helps students in the classroom as well as other engineering practitioners who are approaching these topics for real-world use cases.' Madhu Kurup, Vice President, Indeed.com

Spis treści

Part I. Basic Concepts: 1. Teaching computers to write programs; 2. Python; 3. Cloud computing; Part II. Supervised Learning: 4. Regression; 5. Classification-1; 6. Classification-2; Part III. Unsupervised Learning: 7. Clustering; 8. Dimensionality reduction; Part IV. Neural Networks: 9. Neural networks; 10. Deep learning; Part V. Further explorations: 11. Reinforcement learning; 12. Designing and evaluating ML systems; 13. Responsible AI; Appendices.