How Machines Learn: An Illustrated Guide to Machine Learning

How Machines Learn: An Illustrated Guide to Machine LearningReviews
Author: Helen Edwards
Pub Date: 2016
ISBN: n/a
Pages: 63
Language: English
Format: PDF
Size: 12 Mb

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Artificial intelligence is changing our lives in ways we need to understand. Algorithms govern how we find information, how we learn, how we move, how we buy, what we buy, how we stay healthy, how we meet, whom we meet, how we are treated and what we are treated with. Marketing, analytics, diagnostics, manufacturing, driving, searching, speaking, seeing, hearing are all being disrupted and reshaped by machines that learn. Algorithms that can operate at the speed and scale that data is now generated are now making, what once was impossible, a practical reality.
The goal of this book is to get you up to speed on what drives the artificial intelligence you encounter today so you can understand what makes this field of computer science different from the software engineering of the past. It is aimed at executives who would like to use machine learning in their business and want to understand the underlying mechanics, and for anyone else who wants to understand more about the architectures driving artificial intelligence and machine learning.

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Table of Contents

What is Artificial Intelligence
A Brief History of Artificial Intelligence
What Kinds of Artificial Intelligence Are There?
Machine Learning
Supervised Learning
Unsupervised Learning
Reinforcement Learning
Teaching a Machine to Learn
Inverse Deduction
Neural Networks and Deep Learning
How Do Machines See?
Evolutionary and Genetic Algorithms
Bayesian Algorithms
How Do Machines Converse?
Analogizers
Human Guidance for Machines That Learn
Human Input #1: Knowledge of the Domain
Human Input #2: Engineering the Features
Human Input #3: Dealing with Whether the Model Works Well Enough
Six Tips Before You Get Started
The Last Word