Mathematics for Machine Learning – Marc Peter Deisenroth
Master the mathematical foundations essential for success in the BITS WILP AIML program. Mathematics for Machine Learning by Marc Peter Deisenroth is a must-have textbook that bridges the gap between theory and practical machine learning applications. This book covers the core linear algebra, calculus, probability, and optimization topics that form the backbone of modern AI and ML.
Whether you’re preparing for coursework, projects, or cracking semester exams, this book will help you build strong conceptual clarity and mathematical confidence.
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Recommended for BITS WILP AIML students (Semester 1 & 2)
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Covers Linear Algebra, Multivariate Calculus, Probability Theory & Optimization
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Beginner-friendly explanations with clear visualizations
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Ideal for concept-building and quick revision
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Authored by top ML researchers and educators
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Physical copy – High-quality print and durable binding
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Ships within 7 days across India
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