Machine Learning

Written By Ethem Alpaydin
Machine Learning
  • Publsiher : MIT Press
  • Release : 07 October 2016
  • ISBN : 0262529513
  • Pages : 206 pages
  • Rating : 3/5 from 1 reviews
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Read or download book entitled Machine Learning written by Ethem Alpaydin which was release on 07 October 2016, this book published by MIT Press. Available in PDF, EPUB and Kindle Format. Book excerpt: A concise overview of machine learning—computer programs that learn from data—which underlies applications that include recommendation systems, face recognition, and driverless cars. Today, machine learning underlies a range of applications we use every day, from product recommendations to voice recognition—as well as some we don't yet use everyday, including driverless cars. It is the basis of the new approach in computing where we do not write programs but collect data; the idea is to learn the algorithms for the tasks automatically from data. As computing devices grow more ubiquitous, a larger part of our lives and work is recorded digitally, and as “Big Data” has gotten bigger, the theory of machine learning—the foundation of efforts to process that data into knowledge—has also advanced. In this book, machine learning expert Ethem Alpaydin offers a concise overview of the subject for the general reader, describing its evolution, explaining important learning algorithms, and presenting example applications. Alpaydin offers an account of how digital technology advanced from number-crunching mainframes to mobile devices, putting today's machine learning boom in context. He describes the basics of machine learning and some applications; the use of machine learning algorithms for pattern recognition; artificial neural networks inspired by the human brain; algorithms that learn associations between instances, with such applications as customer segmentation and learning recommendations; and reinforcement learning, when an autonomous agent learns act so as to maximize reward and minimize penalty. Alpaydin then considers some future directions for machine learning and the new field of “data science,” and discusses the ethical and legal implications for data privacy and security.

Machine Learning

Machine Learning
  • Author : Ethem Alpaydin
  • Publisher : MIT Press
  • Release Date : 2016-10-07
  • Total pages : 206
  • ISBN : 0262529513
GET BOOK

Summary : A concise overview of machine learning—computer programs that learn from data—which underlies applications that include recommendation systems, face recognition, and driverless cars. Today, machine learning underlies a range of applications we use every day, from product recommendations to voice recognition—as well as some we don't yet use ...

Machine Learning Algorithms

Machine Learning Algorithms
  • Author : Giuseppe Bonaccorso
  • Publisher : Packt Publishing Ltd
  • Release Date : 2017-07-24
  • Total pages : 360
  • ISBN : 0262529513
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Summary : Build strong foundation for entering the world of Machine Learning and data science with the help of this comprehensive guide About This Book Get started in the field of Machine Learning with the help of this solid, concept-rich, yet highly practical guide. Your one-stop solution for everything that matters in ...

Machine Learning For Dummies

Machine Learning For Dummies
  • Author : John Paul Mueller,Luca Massaron
  • Publisher : John Wiley & Sons
  • Release Date : 2021-02-09
  • Total pages : 464
  • ISBN : 0262529513
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Summary : One of Mark Cuban’s top reads for better understanding A.I. (inc.com, 2021) Your comprehensive entry-level guide to machine learning While machine learning expertise doesn’t quite mean you can create your own Turing Test-proof android—as in the movie Ex Machina—it is a form of artificial intelligence ...

Introduction to Machine Learning

Introduction to Machine Learning
  • Author : Ethem Alpaydin
  • Publisher : MIT Press
  • Release Date : 2020-03-17
  • Total pages : 712
  • ISBN : 0262529513
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Summary : A substantially revised fourth edition of a comprehensive textbook, including new coverage of recent advances in deep learning and neural networks. The goal of machine learning is to program computers to use example data or past experience to solve a given problem. Machine learning underlies such exciting new technologies as ...

Machine Learning in Action

Machine Learning in Action
  • Author : Peter Harrington
  • Publisher : Manning Publications
  • Release Date : 2011-12
  • Total pages : 354
  • ISBN : 0262529513
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Summary : Provides information on the concepts of machine theory, covering such topics as statistical data processing, data visualization, and forecasting....

Human in the Loop Machine Learning

Human in the Loop Machine Learning
  • Author : Robert (Munro) Monarch
  • Publisher : Simon and Schuster
  • Release Date : 2021-07-20
  • Total pages : 424
  • ISBN : 0262529513
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Summary : Human-in-the-Loop Machine Learning lays out methods for humans and machines to work together effectively. Summary Most machine learning systems that are deployed in the world today learn from human feedback. However, most machine learning courses focus almost exclusively on the algorithms, not the human-computer interaction part of the systems. This ...

Building Machine Learning Powered Applications

Building Machine Learning Powered Applications
  • Author : Emmanuel Ameisen
  • Publisher : O'Reilly Media
  • Release Date : 2020-03-06
  • Total pages : 250
  • ISBN : 0262529513
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Summary : Learn the skills necessary to design, build, and deploy applications powered by machine learning. Through the course of this hands-on book, you'll build an example ML-driven application from initial idea to deployed product. Data scientists, software engineers, and product managers with little or no ML experience will learn the tools, ...

Machine Learning Guide for Oil and Gas Using Python

Machine Learning Guide for Oil and Gas Using Python
  • Author : Hoss Belyadi,Alireza Haghighat
  • Publisher : Gulf Professional Publishing
  • Release Date : 2021-04-09
  • Total pages : 476
  • ISBN : 0262529513
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Summary : Machine Learning Guide for Oil and Gas Using Python: A Step-by-Step Breakdown with Data, Algorithms, Codes, and Applications delivers a critical training and resource tool to help engineers understand machine learning theory and practice, specifically referencing use cases in oil and gas. The reference moves from explaining how Python works ...

Python Machine Learning

Python Machine Learning
  • Author : Sebastian Raschka
  • Publisher : Packt Publishing Ltd
  • Release Date : 2015-09-23
  • Total pages : 454
  • ISBN : 0262529513
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Summary : Unlock deeper insights into Machine Leaning with this vital guide to cutting-edge predictive analytics About This Book Leverage Python's most powerful open-source libraries for deep learning, data wrangling, and data visualization Learn effective strategies and best practices to improve and optimize machine learning systems and algorithms Ask – and answer – tough ...

Fundamentals of Machine Learning for Predictive Data Analytics

Fundamentals of Machine Learning for Predictive Data Analytics
  • Author : John D. Kelleher,Brian Mac Namee,Aoife D'Arcy
  • Publisher : MIT Press
  • Release Date : 2015-07-24
  • Total pages : 624
  • ISBN : 0262529513
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Summary : A comprehensive introduction to the most important machine learning approaches used in predictive data analytics, covering both theoretical concepts and practical applications....

Hands On Machine Learning with Scikit Learn Keras and TensorFlow

Hands On Machine Learning with Scikit Learn  Keras  and TensorFlow
  • Author : Aurélien Géron
  • Publisher : O'Reilly Media
  • Release Date : 2019-09-05
  • Total pages : 856
  • ISBN : 0262529513
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Summary : Through a series of recent breakthroughs, deep learning has boosted the entire field of machine learning. Now, even programmers who know close to nothing about this technology can use simple, efficient tools to implement programs capable of learning from data. This practical book shows you how. By using concrete examples, ...

Machine Learning

Machine Learning
  • Author : Peter Flach
  • Publisher : Cambridge University Press
  • Release Date : 2012-09-20
  • Total pages : 409
  • ISBN : 0262529513
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Summary : As one of the most comprehensive machine learning texts around, this book does justice to the field's incredible richness, but without losing sight of the unifying principles. Peter Flach's clear, example-based approach begins by discussing how a spam filter works, which gives an immediate introduction to machine learning in action, ...

Introduction to Machine Learning with Python

Introduction to Machine Learning with Python
  • Author : Andreas C. Müller,Sarah Guido
  • Publisher : "O'Reilly Media, Inc."
  • Release Date : 2016-09-26
  • Total pages : 400
  • ISBN : 0262529513
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Summary : 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 Python, even as a beginner, this book will teach you practical ways to build your own machine learning solutions. With ...

Hands On Machine Learning with C

Hands On Machine Learning with C
  • Author : Kirill Kolodiazhnyi
  • Publisher : Packt Publishing Ltd
  • Release Date : 2020-05-15
  • Total pages : 530
  • ISBN : 0262529513
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Summary : Implement supervised and unsupervised machine learning algorithms using C++ libraries such as PyTorch C++ API, Caffe2, Shogun, Shark-ML, mlpack, and dlib with the help of real-world examples and datasets Key Features Become familiar with data processing, performance measuring, and model selection using various C++ libraries Implement practical machine learning and ...

Machine Learning with Go Quick Start Guide

Machine Learning with Go Quick Start Guide
  • Author : Michael Bironneau,Toby Coleman
  • Publisher : Packt Publishing Ltd
  • Release Date : 2019-05-31
  • Total pages : 168
  • ISBN : 0262529513
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Summary : This quick start guide will bring the readers to a basic level of understanding when it comes to the Machine Learning (ML) development lifecycle, will introduce Go ML libraries and then will exemplify common ML methods such as Classification, Regression, and Clustering Key Features Your handy guide to building machine ...