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Readings in Machine Learning

Author: Jude W. Shavlik

Publisher: Morgan Kaufmann

Published: 1990

Total Pages: 868

ISBN-13: 9781558601437

The ability to learn is a fundamental characteristic of intelligent behavior. Consequently, machine learning has been a focus of artificial intelligence since the beginnings of AI in the 1950s. The 1980s saw tremendous growth in the field, and this growth promises to continue with valuable contributions to science, engineering, and business. Readings in Machine Learning collects the best of the published machine learning literature, including papers that address a wide range of learning tasks, and that introduce a variety of techniques for giving machines the ability to learn. The editors, in cooperation with a group of expert referees, have chosen important papers that empirically study, theoretically analyze, or psychologically justify machine learning algorithms. The papers are grouped into a dozen categories, each of which is introduced by the editors.

Machine Reading Comprehension

Author: Chenguang Zhu

Publisher: Elsevier

Published: 2021-03-20

Total Pages: 272

ISBN-13: 0323901190

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Machine reading comprehension (MRC) is a cutting-edge technology in natural language processing (NLP). MRC has recently advanced significantly, surpassing human parity in several public datasets. It has also been widely deployed by industry in search engine and quality assurance systems. Machine Reading Comprehension: Algorithms and Practice performs a deep-dive into MRC, offering a resource on the complex tasks this technology involves. The title presents the fundamentals of NLP and deep learning, before introducing the task, models, and applications of MRC. This volume gives theoretical treatment to solutions and gives detailed analysis of code, and considers applications in real-world industry. The book includes basic concepts, tasks, datasets, NLP tools, deep learning models and architecture, and insight from hands-on experience. In addition, the title presents the latest advances from the past two years of research. Structured into three sections and eight chapters, this book presents the basis of MRC; MRC models; and hands-on issues in application. This book offers a comprehensive solution for researchers in industry and academia who are looking to understand and deploy machine reading comprehension within natural language processing. Presents the first comprehensive resource on machine reading comprehension (MRC) Performs a deep-dive into MRC, from fundamentals to latest developments Offers the latest thinking and research in the field of MRC, including the BERT model Provides theoretical discussion, code analysis, and real-world applications of MRC Gives insight from research which has led to surpassing human parity in MRC

Readings in Knowledge Acquisition and Learning

Author: Bruce G. Buchanan

Publisher: Morgan Kaufmann Publishers

Published: 1993

Total Pages: 926

ISBN-13:

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Readings in Knowledge Acquisition and Learning collects the best of the artificial intelligence literature from the fields of machine learning and knowledge acquisition. This book brings together the perspectives on constructing knowledge-based systems from these two historically separate subfields of artificial intelligence.

Elements of Machine Learning

Author: Pat Langley

Publisher: Morgan Kaufmann

Published: 1996

Total Pages: 436

ISBN-13: 9781558603011

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Machine learning is the computational study of algorithms that improve performance based on experience, and this book covers the basic issues of artificial intelligence. Individual sections introduce the basic concepts and problems in machine learning, describe algorithms, discuss adaptions of the learning methods to more complex problem-solving tasks and much more.

Machine Learning For Dummies

Author: John Paul Mueller

Publisher: John Wiley & Sons

Published: 2021-02-09

Total Pages: 471

ISBN-13: 1119724015

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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 and one of the most exciting technological means of identifying opportunities and solving problems fast and on a large scale. Anyone who masters the principles of machine learning is mastering a big part of our tech future and opening up incredible new directions in careers that include fraud detection, optimizing search results, serving real-time ads, credit-scoring, building accurate and sophisticated pricing models—and way, way more. Unlike most machine learning books, the fully updated 2nd Edition of Machine Learning For Dummies doesn't assume you have years of experience using programming languages such as Python (R source is also included in a downloadable form with comments and explanations), but lets you in on the ground floor, covering the entry-level materials that will get you up and running building models you need to perform practical tasks. It takes a look at the underlying—and fascinating—math principles that power machine learning but also shows that you don't need to be a math whiz to build fun new tools and apply them to your work and study. Understand the history of AI and machine learning Work with Python 3.8 and TensorFlow 2.x (and R as a download) Build and test your own models Use the latest datasets, rather than the worn out data found in other books Apply machine learning to real problems Whether you want to learn for college or to enhance your business or career performance, this friendly beginner's guide is your best introduction to machine learning, allowing you to become quickly confident using this amazing and fast-developing technology that's impacting lives for the better all over the world.

Machine Learning

Author: Abdelhamid Mellouk

Publisher: BoD – Books on Demand

Published: 2009-01-01

Total Pages: 434

ISBN-13: 3902613564

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Machine Learning can be defined in various ways related to a scientific domain concerned with the design and development of theoretical and implementation tools that allow building systems with some Human Like intelligent behavior. Machine learning addresses more specifically the ability to improve automatically through experience.

Machine Learning

Author: Anthony Aline

Publisher:

Published: 2019-03-29

Total Pages: 108

ISBN-13: 9781091948068

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★★Buy the Paperback Version of this Book and get the Kindle Book version for FREE ★★ Artificial Intelligence, and in particular, Machine Learning is here today and it is shaping our world. It is shaping and simplifying the way we live, work, travel and communicate. Hence it is important for you to understand what it is and how it works. This guide has been designed to help you gain an understanding of machine learning, artificial intelligence and big data in a simple way. We will walk you step-by-step into the world of Machine Learning. You will have the opportunity to develop new skills and improve your understanding of this challenging yet lucrative sub-field of machine learning. The content presented in this eBook has been prepared for the total beginner and it doesn't matter who you are or whatever job you are currently doing. This e-book will also be of great benefit to you if you are a business owner. No matter who you are or what you are doing currently, Machine learning can be understood by anyone. This E-book is recommended for you so long you have an interest in machine learning. This introductory guide on machine learning is fun and exciting, but at the same time we dive deep into Machine Learning in a structured way. This guide us easy to read and after reading the whole guide you should have in-depth understanding of the following: Gain an in-depth understanding of Machine Learning, Data Science, Neural Networks, Artificial Intelligence and Neural networks Have a great understanding of many Machine Learning models Know about how accurate prediction are made using machine learning Know the myth various machine learning myths Have a great understanding of how giant companies like Amazon and Netflix, Facebook and twitter are using machine learning Understand the applications of machine learning Scroll Up and Click the Buy Now Button!

Encyclopedia of Machine Learning

Author: Claude Sammut

Publisher: Springer Science & Business Media

Published: 2011-03-28

Total Pages: 1061

ISBN-13: 0387307680

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This comprehensive encyclopedia, in A-Z format, provides easy access to relevant information for those seeking entry into any aspect within the broad field of Machine Learning. Most of the entries in this preeminent work include useful literature references.

Readings in Cognitive Science

Author: Allan Collins

Publisher: Elsevier

Published: 2013-10-02

Total Pages: 672

ISBN-13: 148321446X

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Readings in Cognitive Science: A Perspective from Psychology and Artificial Intelligence brings together important studies that fall in the intersection between artificial intelligence and cognitive psychology. This book is composed of six chapters, and begins with the complex anatomy and physiology of the human brain. The next chapters deal with the components of cognitive science, such as the semantic memory, similarity and analogy, and learning. These chapters also consider the application of mental models, which represent the domain-specific knowledge needed to understand a dynamic system or natural physical phenomena. The remaining chapters discuss the concept of reasoning, problem solving, planning, vision, and imagery. This book is of value to psychologists, psychiatrists, neurologists, and researchers who are interested in cognition.

Machine Learning

Author: Brian L. Taylor

Publisher:

Published: 2019-07-07

Total Pages: 77

ISBN-13: 9781079189384

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★★★ Buy the Paperback version and then get the Kindle Book versions for FREE ★★★ Do you want to know, How to work with Robot Program? Do you want to become an expert Robot/Machine Programmer? And impress your friends with the programs you can make from scratch, Then you are on the right way and keep reading this Machine Learning book. From self-driving cars, recommendation systems to face and voice recognition, machine learning is the direction of the future. Would you choose to learn the mathematics behind machine learning to enter the fields of data analysis and artificial intelligence? There are not many resources that give detailed and straightforward examples and that go step by step through the topics of machine learning. If you are read this "Machine Learning: a quick guide to Artificial Intelligence, Neural Network and Cutting Edge Deep Learning Techniques for beginners", you are at the right place. This book not only explains what kind of mathematics is involved and the confusing notation, but also directly presents the fundamental topics of machine learning. This book will help you to learn smoothly and naturally, that will prepare you for more advanced topics besides taking away the belief that machine learning is complicated and difficult. In this book, you will attain helpful information for getting started, such as: Criteria that help distinguish tasks that are suitable for machine Supervised Machine Learning Neural Networks Unsupervised Machine Learning Learning by Reinforcement Neural Networks Neural Networks versus Conventional Computers Deep Learning Supervised Modes and Unsupervised Modes Running Python Getting Started Artificial Intelligence, Machine Learning, and Deep Learning The Future Promise of Artificial Intelligence and deep learning and more How many hours of your life are you willing to waste to gather partial or false information when you can get everything you require to REACH YOUR GOALS by reading this fantastic guide. Get Your Copy Now! Scroll Up and Click the Buy Now Button And Enjoy!