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 : 32,7 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 : 50,7 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.

Calculus for Machine Learning

Calculus for Machine Learning
  • Publisher : Machine Learning Mastery
  • File Size : 27,5 Mb
  • Release Date : 23 February 2022
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Calculus seems to be obscure, but it is everywhere. In machine learning, while we rarely write code on differentiation or integration, the algorithms we use have theoretical roots in calculus.

Introduction to Deep Learning

Introduction to Deep Learning
  • Publisher : Springer
  • File Size : 37,6 Mb
  • Release Date : 04 February 2018
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This textbook presents a concise, accessible and engaging first introduction to deep learning, offering a wide range of connectionist models which represent the current state-of-the-art. The text explores the most

Deep Learning Illustrated

Deep Learning Illustrated
  • Publisher : Addison-Wesley Professional
  • File Size : 39,8 Mb
  • Release Date : 05 August 2019
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"The authors’ clear visual style provides a comprehensive look at what’s currently possible with artificial neural networks as well as a glimpse of the magic that’s to come." –

Hands-On Mathematics for Deep Learning

Hands-On Mathematics for Deep Learning
  • Publisher : Packt Publishing Ltd
  • File Size : 29,9 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

Deep Learning for Coders with fastai and PyTorch

Deep Learning for Coders with fastai and PyTorch
  • Publisher : O'Reilly Media
  • File Size : 43,6 Mb
  • Release Date : 29 June 2020
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Deep learning is often viewed as the exclusive domain of math PhDs and big tech companies. But as this hands-on guide demonstrates, programmers comfortable with Python can achieve impressive results

Math for Deep Learning

Math for Deep Learning
  • Publisher : No Starch Press
  • File Size : 31,7 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

Probability Inequalities

Probability Inequalities
  • Publisher : Springer Science & Business Media
  • File Size : 55,6 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

Mathematics and Programming for Machine Learning with R

Mathematics and Programming for Machine Learning with R
  • Publisher : CRC Press
  • File Size : 23,8 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

Basics of Linear Algebra for Machine Learning

Basics of Linear Algebra for Machine Learning
  • Publisher : Machine Learning Mastery
  • File Size : 44,9 Mb
  • Release Date : 24 January 2018
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Linear algebra is a pillar of machine learning. You cannot develop a deep understanding and application of machine learning without it. In this laser-focused Ebook, you will finally cut through