▶Book Description
AI is changing the world – and with this book, anyone can start building intelligent software!
Through his best-selling video courses, Hadelin de Ponteves has taught hundreds of thousands of people to write AI software. Now, for the first time, his hands-on, energetic approach is available as a book. Taking a graduated approach that starts with the basics before easing readers into more complicated formulas and notation, Hadelin helps you understand what you really need to build AI systems with reinforcement learning and deep learning. Five full working projects put the ideas into action, showing step-by-step how to build intelligent software using the best and easiest tools for AI programming:
- Google Colab
- Python
- TensorFlow
- Keras
- PyTorch
AI Crash Course teaches everyone to build an AI to work in their applications. Once you've read this book, you're only limited by your imagination.
▶What You Will Learn
- Master the key skills of deep learning, reinforcement learning, and deep reinforcement learning
- Understand Q-learning and deep Q-learning
- Learn from friendly, plain English explanations and practical activities
- Build fun projects, including a virtual-self-driving car
- Use AI to solve real-world business problems and win classic video games
- Build an intelligent, virtual robot warehouse worker
▶Key Features
- Roll up your sleeves and start programming AI models
- No math, data science, or machine learning background required
- Packed with hands-on examples, illustrations, and clear step-by-step instructions
- 5 hands-on working projects put ideas into action and show step-by-step how to build intelligent software
▶Who This Book Is For
If you want to add AI to your skillset, this book is for you. It doesn't require data science or machine learning knowledge. Just maths basics (high school level).
▶What this book covers
- Chapter 1, Welcome to the Robot World, introduces you to the world of Artificial Intelligence.
- Chapter 2, Discover Your AI Toolkit, uncovers an easy-to-use toolkit of all the AI models as Python files, ready to run thanks to the amazing Google Colaboratory platform.
- Chapter 3, Python Fundamentals – Learn How to Code in Python, provides the right Python fundamentals and teaches you how to code in Python.
- Chapter 4, AI Foundation Techniques, introduces you to reinforcement learning and its five fundamental principles.
- Chapter 5, Your First AI Model – Beware the Bandits!, teaches the theory of the multiarmed bandit problem and how to solve it in the best way with the Thompson Sampling AI model.
- Chapter 6, AI for Sales and Advertising – Sell like the Wolf of AI Street, applies the Thompson Sampling AI model of Chapter 5 to solve a real-world business problem related to sales and advertising.
- Chapter 7, Welcome to Q-Learning, introduces the theory of the Q-learning AI model.
- Chapter 8, AI for Logistics – Robots in a Warehouse, applies the Q-learning AI model of Chapter 7 to solve a real-world business problem related to logistics optimization.
- Chapter 9, Going Pro with Artificial Brains – Deep Q-Learning, introduces the fundamentals of deep learning and the theory of the deep Q-learning AI model.
- Chapter 10, AI for Autonomous Vehicles – Build a Self-Driving Car, applies the deep Q-learning AI model of Chapter 9 to build a virtual self-driving car.
- Chapter 11, AI for Business – Minimize Cost with Deep Q-Learning, applies the deep Q-learning AI model of Chapter 9 to solve a real-world business problem related to cost optimization.
- Chapter 12, Deep Convolutional Q-Learning, introduces the fundamentals of convolutional neural networks and the theory of the deep convolutional Q-learning AI model.
- Chapter 13, AI for Games – Become the Master at Snake, applies the deep convolutional Q-learning AI model of Chapter 12 to beat the famous Snake video game.
- Chapter 14, Recap and Conclusion, concludes the book with a recap of how to create an AI framework and some final words from the author about your future in the world of AI.
