Features:
Provides an easy-to-read presentation of commonly used machine learning algorithms in a manner suitable for advanced undergraduate or beginning graduate students, and mathematically and/or programming-oriented individuals who want to learn machine learning on their own.
Covers mathematical details of the machine learning algorithms discussed to ensure firm understanding, enabling further exploration
Presents worked out suitable programming examples, thus ensuring conceptual, theoretical and practical understanding of the machine learning methods.
This book is aimed primarily at introducing essential topics in Machine Learning to advanced undergraduates and beginning graduate students. The number of topics has been kept deliberately small so that it can all be covered in a semester or a quarter. The topics are covered in depth, within limits of what can be taught in a short period of time. Thus, the book can provide foundations that will empower a student to read advanced books and research papers.

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