£45.51

Springer Linear Algebra and Optimization for Machine Learning

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£69.43 £43.12 £48.86 £54.60 £60.34 £66.08 £71.82 08 July 2026 30 July 2026 21 August 2026 12 September 2026 05 October 2026

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Description

Master the mathematical foundations of modern artificial intelligence with this comprehensive textbook from Springer. Designed specifically for the intersection of mathematics and computer science, this book provides a deep dive into linear algebra and optimization techniques as they apply directly to machine learning workflows. By focusing on practical applications, the text helps students bridge the gap between theoretical math and real-world data science implementation. The content is structured to support academic growth, making it an ideal resource for graduate-level students and professors in computer science, mathematics, and data science. Advanced undergraduate students will also find the material accessible and highly relevant to their studies. Each chapter includes practical examples and exercises to reinforce learning. For instructors, a dedicated solution manual for the end-of-chapter exercises is available, making it a complete package for classroom instruction and self-study in higher education settings.

Key Features

Targeted academic content designed for graduate students and professors in computer science, mathematics, and data science.

Practical learning through integrated examples and exercises provided throughout the text to reinforce complex concepts.

Comprehensive coverage of linear algebra and its specific applications within the field of machine learning.

Suitable for advanced undergraduate students looking to build a strong mathematical foundation for technical studies.

Instructor support including a solution manual for all exercises found at the end of each chapter.

Product Specifications

Format
hardcover
Domain
Amazon UK
Release Date
13 May 2020
Listed Since
25 December 2019

Barcode

No barcode data available

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