An Introduction to Machine Learning Book [PDF] Download

Download the fantastic book titled An Introduction to Machine Learning written by Miroslav Kubat, 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 "An Introduction to Machine Learning", which was released on 25 September 2021. We suggest perusing the summary before initiating your download. This book is a top selection for enthusiasts of the Computers genre.

Summary of An Introduction to Machine Learning by Miroslav Kubat PDF

This textbook offers a comprehensive introduction to Machine Learning techniques and algorithms. This Third Edition covers newer approaches that have become highly topical, including deep learning, and auto-encoding, introductory information about temporal learning and hidden Markov models, and a much more detailed treatment of reinforcement learning. The book is written in an easy-to-understand manner with many examples and pictures, and with a lot of practical advice and discussions of simple applications. The main topics include Bayesian classifiers, nearest-neighbor classifiers, linear and polynomial classifiers, decision trees, rule-induction programs, artificial neural networks, support vector machines, boosting algorithms, unsupervised learning (including Kohonen networks and auto-encoding), deep learning, reinforcement learning, temporal learning (including long short-term memory), hidden Markov models, and the genetic algorithm. Special attention is devoted to performance evaluation, statistical assessment, and to many practical issues ranging from feature selection and feature construction to bias, context, multi-label domains, and the problem of imbalanced classes.


Detail About An Introduction to Machine Learning PDF

  • Author : Miroslav Kubat
  • Publisher : Springer Nature
  • Genre : Computers
  • Total Pages : 458 pages
  • ISBN : 3030819353
  • PDF File Size : 9,5 Mb
  • Language : English
  • Rating : 4/5 from 21 reviews

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An Introduction to Machine Learning

An Introduction to Machine Learning
  • Publisher : Springer Nature
  • File Size : 30,6 Mb
  • Release Date : 25 September 2021
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This textbook offers a comprehensive introduction to Machine Learning techniques and algorithms. This Third Edition covers newer approaches that have become highly topical, including deep learning, and auto-encoding, introductory information

An Introduction to Machine Learning

An Introduction to Machine Learning
  • Publisher : Springer
  • File Size : 24,6 Mb
  • Release Date : 07 May 2019
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Just like electricity, Machine Learning will revolutionize our life in many ways – some of which are not even conceivable today. This book provides a thorough conceptual understanding of Machine Learning

Introduction to Machine Learning

Introduction to Machine Learning
  • Publisher : MIT Press
  • File Size : 54,8 Mb
  • Release Date : 22 August 2014
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Introduction -- Supervised learning -- Bayesian decision theory -- Parametric methods -- Multivariate methods -- Dimensionality reduction -- Clustering -- Nonparametric methods -- Decision trees -- Linear discrimination -- Multilayer

Introduction to Deep Learning

Introduction to Deep Learning
  • Publisher : MIT Press
  • File Size : 32,8 Mb
  • Release Date : 29 January 2019
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A project-based guide to the basics of deep learning. This concise, project-driven guide to deep learning takes readers through a series of program-writing tasks that introduce them to the use

Reinforcement Learning, second edition

Reinforcement Learning, second edition
  • Publisher : MIT Press
  • File Size : 45,7 Mb
  • Release Date : 13 November 2018
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The significantly expanded and updated new edition of a widely used text on reinforcement learning, one of the most active research areas in artificial intelligence. Reinforcement learning, one of the

A Concise Introduction to Machine Learning

A Concise Introduction to Machine Learning
  • Publisher : CRC Press
  • File Size : 20,5 Mb
  • Release Date : 01 August 2019
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The emphasis of the book is on the question of Why – only if why an algorithm is successful is understood, can it be properly applied, and the results trusted. Algorithms

Deep Learning

Deep Learning
  • Publisher : MIT Press
  • File Size : 55,6 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

Introduction to Machine Learning with Python

Introduction to Machine Learning with Python
  • Publisher : "O'Reilly Media, Inc."
  • File Size : 27,7 Mb
  • Release Date : 26 September 2016
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Machine learning has become an integral part of many commercial applications and research projects, but this field is not exclusive to large companies with extensive research teams. If you use

Introduction to Machine Learning with R

Introduction to Machine Learning with R
  • Publisher : "O'Reilly Media, Inc."
  • File Size : 29,5 Mb
  • Release Date : 07 March 2018
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Machine learning is an intimidating subject until you know the fundamentals. If you understand basic coding concepts, this introductory guide will help you gain a solid foundation in machine learning

Introduction to Deep Learning

Introduction to Deep Learning
  • Publisher : Springer
  • File Size : 27,8 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