Mathematics for Machine Learning Book [PDF] Download

• Publisher : Cambridge University Press
• File Size : 38,6 Mb
• Release Date : 23 April 2020

Distills key concepts from linear algebra, geometry, matrices, calculus, optimization, probability and statistics that are used in machine learning.

• Publisher : Packt Publishing Ltd
• File Size : 34,7 Mb
• Release Date : 12 June 2020

A comprehensive guide to getting well-versed with the mathematical techniques for building modern deep learning architectures Key FeaturesUnderstand linear algebra, calculus, gradient algorithms, and other concepts essential for training deep

• Publisher : Unknown Publisher
• File Size : 47,6 Mb
• Release Date : 20 May 2019

Machine Learning: An Applied Mathematics Introduction covers the essential mathematics behind all of the following topics - K Nearest Neighbours; K Means Clustering; Naïve Bayes Classifier; Regression Methods; Support

• Publisher : CRC Press
• File Size : 52,6 Mb
• Release Date : 26 October 2020

Based on the author’s experience in teaching data science for more than 10 years, Mathematics and Programming for Machine Learning with R: From the Ground Up reveals how machine learning

• Publisher : Simon and Schuster
• File Size : 53,8 Mb
• Release Date : 21 May 2024

Shine a spotlight into the deep learning “black box”. This comprehensive and detailed guide reveals the mathematical and architectural concepts behind deep learning models, so you can customize, maintain, and

• Publisher : No Starch Press
• File Size : 52,7 Mb
• Release Date : 07 December 2021

Math for Deep Learning provides the essential math you need to understand deep learning discussions, explore more complex implementations, and better use the deep learning toolkits. With Math for Deep

• Publisher : CRC Press
• File Size : 29,8 Mb
• Release Date : 20 November 2019

Focuses on mathematical understanding Presentation is self-contained, accessible, and comprehensive Full color throughout Extensive list of exercises and worked-out examples Many concrete algorithms with actual code

• Publisher : Springer Science & Business Media
• File Size : 41,9 Mb
• Release Date : 30 May 2011

Inequality has become an essential tool in many areas of mathematical research, for example in probability and statistics where it is frequently used in the proofs. "Probability Inequalities" covers inequalities

• Publisher : MIT Press
• File Size : 20,8 Mb
• Release Date : 10 November 2016

An introduction to a broad range of topics in deep learning, covering mathematical and conceptual background, deep learning techniques used in industry, and research perspectives. “Written by three experts in

• Publisher : Springer Nature
• File Size : 44,9 Mb
• Release Date : 13 May 2020

This textbook introduces linear algebra and optimization in the context of machine learning. Examples and exercises are provided throughout the book. A solution manual for the exercises at the end