Machine Learning, 2/e

Machine Learning introduces readers to the area of machine learning in an extremely easy to read and understand manner. Through numerous worked-out problems, diagrams and notes, the text makes this challenging subject easy to assimilate. The text starts with a simple introduction to the concepts of machine learning and expands it by delving into the details of different learning algorithms by using sample caselets. The authors, by virtue of their long exposure to industry implementations, have designed the topics so that readers will earn industry-readiness by just reading this text.

Features –

Generative AI and Large Language Models with emphasis on Prompt Engineering

Reinforcement learning

End-end Machine Learning Implementation

About the Author

Saikat Dutt - Visiting Faculty, Indian Institute of Management Calcutta, Former Senior Director, Cognizant Technology Solutions

Subramanian Chandramouli - Associate Director, Cognizant Technology Solutions

Amit Kumar Das Principal Director, LTIMindtree Former Faculty Member, Institute of Engineering & Management, Kolkata

Book Contents –

1. Introduction to Machine Learning 2. Preparing to Model 3. Modelling and Evaluation 4. Basics of Feature Engineering 5. Brief Overview of Probability 6. Bayesian Concept Learning 7. Supervised Learning: Classification 8. Supervised Learning: Regression 9. Unsupervised Learning 10. Reinforcement Learning 11. Basics of Neural Network 12. Other Types of Learning 13. End-to-end ML implementations 14. Generative AI & Large Language Models