更新时间：2021-03-26 16:23:07
封面
AI Crash Course
Why subscribe?
Contributors
About the author
About the reviewers
Preface
Who this book is for
What this book covers
To get the most out of this book
Get in touch
1 Welcome to the Robot World
Beginning the AI journey
Four different AI models
Where can learning AI take you?
Summary
2 Discover Your AI Toolkit
The GitHub page
Colaboratory
3 Python Fundamentals – Learn How to Code in Python
Displaying text
Variables and operations
Lists and arrays
if statements and conditions
for and while loops
Functions
Classes and objects
4 AI Foundation Techniques
What is Reinforcement Learning?
The five principles of Reinforcement Learning
5 Your First AI Model – Beware the Bandits!
The multi-armed bandit problem
The Thompson Sampling model
6 AI for Sales and Advertising – Sell like the Wolf of AI Street
Problem to solve
Building the environment inside a simulation
AI solution and intuition refresher
Implementation
7 Welcome to Q-Learning
The Maze
The whole Q-learning process
8 AI for Logistics – Robots in a Warehouse
Building the environment
9 Going Pro with Artificial Brains – Deep Q-Learning
Predicting house prices
Deep learning theory
Deep Q-learning
10 AI for Autonomous Vehicles – Build a Self-Driving Car
AI solution refresher
The demo
11 AI for Business – Minimize Costs with Deep Q-Learning
AI solution
Recap – The general AI framework/Blueprint
12 Deep Convolutional Q-Learning
What are CNNs used for?
How do CNNs work?
Deep convolutional Q-learning
Chapter 13 AI for Games – Become the Master at Snake
14 Recap and Conclusion
Recap – The general AI framework/blueprint
Exploring what's next for you in AI
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