Mathematics for Machine Learning

  • Publisher : Cambridge University Press
  • File Size : 54,7 Mb
  • Release : 23 April 2020
  • ISBN : 9781108470049
  • Page : 391 pages
  • Rating : 5/5 (1 users)

Summary: Mathematics for Machine Learning PDF is a Fantastic Computers book by Marc Peter Deisenroth. It was published by Cambridge University Press on 23 April 2020. This Book has 391 pages and Available to download in PDF, EPUB and Kindle Format. Read detail book and summary below and click download button to get book file and read directly from your devices.

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

Mathematics for Machine Learning

Mathematics for Machine Learning
Author: Marc Peter Deisenroth,A. Aldo Faisal,Cheng Soon Ong
File Size : 44,5 Mb
Category: Computers

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

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Mathematics for Machine Learning

Mathematics for Machine Learning
Author: Marc Peter Deisenroth,A. Aldo Faisal,Cheng Soon Ong
File Size : 54,6 Mb
Category: Computers

The fundamental mathematical tools needed to understand machine learning include linear algebra, analytic geometry, matrix decompositions, vector calculus, optimization, probability and statistics. These topics are traditionally taught in disparate courses,

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Hands On Mathematics for Deep Learning

Hands On Mathematics for Deep Learning
Author: Jay Dawani
File Size : 45,5 Mb
Category: Computers

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

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Machine Learning

Machine Learning
Author: Paul Wilmott
File Size : 54,7 Mb
Category: Computers

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

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Math for Deep Learning

Math for Deep Learning
Author: Ronald T. Kneusel
File Size : 52,8 Mb
Category: Computers

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

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Mathematics and Programming for Machine Learning with R

Mathematics and Programming for Machine Learning with R
Author: William B. Claster
File Size : 43,5 Mb
Category: Computers

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

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Data Science and Machine Learning

Data Science and Machine Learning
Author: Dirk P. Kroese,Zdravko Botev,Thomas Taimre,Radislav Vaisman
File Size : 47,9 Mb
Category: Computers

"This textbook is a well-rounded, rigorous, and informative work presenting the mathematics behind modern machine learning techniques. It hits all the right notes: the choice of topics is up-to-date and

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Machine Learning with Spark Second Edition

Machine Learning with Spark   Second Edition
Author: Rajdeep Dua,Manpreet Singh Ghotra,Nick Pentreath
File Size : 53,6 Mb
Category: Computers

Develop intelligent machine learning systems with SparkAbout This Book*Get to the grips with the latest version of Apache Spark*Utilize Spark's machine learning library to implement predictive analytics*Leverage

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Math and Architectures of Deep Learning

Math and Architectures of Deep Learning
Author: Krishnendu Chaudhury
File Size : 43,5 Mb
Category: Computers

Math and Architectures of Deep Learning sets out the foundations of DL usefully and accessibly to working practitioners. Math and Architectures of Deep Learning bridges the gap between theory and

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Math for Machine Learning

Math for Machine Learning
Author: Richard Han
File Size : 47,5 Mb
Category: Computers

This book explains the math behind machine learning using simple but concrete examples. This book will get you started in machine learning in a smooth and natural way, preparing you

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Understanding Machine Learning

Understanding Machine Learning
Author: Shai Shalev-Shwartz,Shai Ben-David
File Size : 50,7 Mb
Category: Computers

Introduces machine learning and its algorithmic paradigms, explaining the principles behind automated learning approaches and the considerations underlying their usage.

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Mathematical Theories of Machine Learning Theory and Applications

Mathematical Theories of Machine Learning   Theory and Applications
Author: Bin Shi,S. S. Iyengar
File Size : 53,6 Mb
Category: Computers

This book studies mathematical theories of machine learning. The first part of the book explores the optimality and adaptivity of choosing step sizes of gradient descent for escaping strict saddle

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Machine Learning Mathematics

Machine Learning Mathematics
Author: Samuel Hack
File Size : 40,5 Mb
Category: Computers

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Deep Learning

Deep Learning
Author: Ian Goodfellow,Yoshua Bengio,Aaron Courville
File Size : 40,6 Mb
Category: Computers

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

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Linear Algebra and Optimization for Machine Learning

Linear Algebra and Optimization for Machine Learning
Author: Charu C. Aggarwal
File Size : 42,6 Mb
Category: Computers

This textbook introduces linear algebra and optimization in the context of machine learning. Examples and exercises are provided throughout this text book together with access to a solution’s manual.

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