£41.62

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£42 today · all-time low £42 (Jul 2026) · usually the usual

Springer Linear Algebra and Optimization for Machine Learning

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Description

Master the mathematical foundations of machine learning with this second edition textbook from Springer. Designed specifically to address the challenges beginners face, this edition provides a streamlined approach to linear algebra and optimization. Unlike standard mathematics courses that cover broad topics unnecessary for data science, this book focuses on the material most relevant to machine learning applications. The second edition features a simplified exposition compared to the 2020 original, making complex concepts easier to grasp. To support your learning and practical application, the text is enhanced with a large number of solved examples and exercises. This makes it an ideal resource for students and professionals looking to bridge the gap between theoretical mathematics and practical machine learning implementation.

Key Features

This second edition from Springer provides a simplified exposition of linear algebra and optimization compared to the 2020 version.

The textbook includes a large number of solved examples to help learners understand complex mathematical concepts.

Extensive exercises are integrated into the text to reinforce learning and practical application of the material.

The content is specifically tailored to machine learning, avoiding the unnecessary material found in general mathematics courses.

This book serves as a targeted resource for beginners who need a specific background in optimization and linear algebra.

Product Specifications

Format
hardcover
Domain
Amazon UK
Release Date
24 September 2025
Listed Since
04 June 2025

Barcode

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