Mathematics for Machine Learning Book [PDF] Download

Download the fantastic book titled Mathematics for Machine Learning written by Marc Peter Deisenroth, available in its entirety in both PDF and EPUB formats for online reading. This page includes a concise summary, a preview of the book cover, and detailed information about "Mathematics for Machine Learning", which was released on 23 April 2020. We suggest perusing the summary before initiating your download. This book is a top selection for enthusiasts of the Computers genre.

Summary of Mathematics for Machine Learning by Marc Peter Deisenroth PDF

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


Detail About Mathematics for Machine Learning PDF

  • Author : Marc Peter Deisenroth
  • Publisher : Cambridge University Press
  • Genre : Computers
  • Total Pages : 391 pages
  • ISBN : 1108470041
  • PDF File Size : 19,6 Mb
  • Language : English
  • Rating : 5/5 from 1 reviews

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Mathematics for Machine Learning

Mathematics for Machine Learning
  • Publisher : Cambridge University Press
  • File Size : 40,7 Mb
  • Release Date : 23 April 2020
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Distills key concepts from linear algebra, geometry, matrices, calculus, optimization, probability and statistics that are used in machine learning.

Hands-On Mathematics for Deep Learning

Hands-On Mathematics for Deep Learning
  • Publisher : Packt Publishing Ltd
  • File Size : 39,8 Mb
  • Release Date : 12 June 2020
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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

Math for Deep Learning

Math for Deep Learning
  • Publisher : No Starch Press
  • File Size : 29,5 Mb
  • Release Date : 07 December 2021
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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

Mathematics and Programming for Machine Learning with R

Mathematics and Programming for Machine Learning with R
  • Publisher : CRC Press
  • File Size : 20,9 Mb
  • Release Date : 26 October 2020
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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

Machine Learning

Machine Learning
  • Publisher : Unknown Publisher
  • File Size : 33,9 Mb
  • Release Date : 20 May 2019
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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

Math and Architectures of Deep Learning

Math and Architectures of Deep Learning
  • Publisher : Simon and Schuster
  • File Size : 20,6 Mb
  • Release Date : 21 May 2024
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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

Data Science and Machine Learning

Data Science and Machine Learning
  • Publisher : CRC Press
  • File Size : 47,9 Mb
  • Release Date : 20 November 2019
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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

Deep Learning

Deep Learning
  • Publisher : MIT Press
  • File Size : 53,5 Mb
  • Release Date : 10 November 2016
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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

Linear Algebra and Optimization for Machine Learning

Linear Algebra and Optimization for Machine Learning
  • Publisher : Springer Nature
  • File Size : 30,7 Mb
  • Release Date : 13 May 2020
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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

Probability Inequalities

Probability Inequalities
  • Publisher : Springer Science & Business Media
  • File Size : 41,7 Mb
  • Release Date : 30 May 2011
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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