Machine Learning for Beginners: Absolute Beginners Guide, Learn Machine Learning and Artificial Intelligence from Scratch

Sebastian, Chris

ISBN 10: 1793016429 / ISBN 13: 9781793016423

Verlag: INDEPENDENTLY PUBLISHED, 2019

Beschreibung

Bestandsnummer des Verkäufers 265995458

Bibliografische Details

• Titel: Machine Learning for Beginners: Absolute Beginners Guide, Learn Machine Learning and Artificial Intelligence from Scratch
• Verlag: INDEPENDENTLY PUBLISHED
• Erscheinungsjahr: 2019
• Sprache: Englisch
• ISBN-10: 1793016429
• ISBN-13: 9781793016423
• Einband: Softcover
• Zustand: New

Über diesen Titel

Inhaltsangabe

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Machine Learning is changing the world.

You use Machine Learning every day and probably don’t know it.

In this book, you will learn how ML grew from a desire to make computers able to learn.

Trace the development of Machine Learning from the early days of a computer learning how to play checkers, to machines able to beat world masters in chess and go. Understand how large data is so important to Machine Learning, and how the collection of massive amounts of data provides Machine Learning programmers with the information they need to developing learning algorithms.Simple examples will help you understand the complex math and probability statistics underlining Machine Learning. You will also see real-world examples of Machine Learning in action and uncover how these algorithms are making your life better every day.Learn about how artificial intelligence, Machine Learning, Neural Networks, and Swarm Intelligence interact and complement each other as part of the quest to generate machines capable of thinking and reacting to the world. Read about the technical issues with Machine Learning and how they are being overcome. Discover the dark side of ML and what possible outcomes there could be should things go wrong. And finally, learn about the positive future artificial intelligence and Machine Learning promise to bring to the world.

In this book, you will discover

•The history of Machine Learning

•Approaches taken to ML in the past and present

•Artificial intelligence and its relationship to ML

•How neural networks, big data, regression, and the cloud all play a part in the development of Machine Learning

•Compare Machine Learning to the Internet of Things, Robotics, and Swarm Intelligence

•Learn about the different models of ML and how each is used to produce learning algorithms

•Get access to free software and data sets so you can try out your very own Machine Learning software

•Examine some of the technical problems and philosophical dilemmas with ML

•See what advanced Machine Learning will make to our world in the future

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