Hands-On Deep Learning for Games

Game development is also a key area where these techniques are being applied. Hands-On Deep Learning for Games will give an in depth view of the potential of deep learning and neural networks in game development. (Limited-time offer)

Table of Contents

• Section 1: The Basics
• Deep Learning for Games
• Convolutional and Recurrent Networks
• GAN for Games
• Building a Deep Learning Gaming Chatbot
• Section 2: Deep Reinforcement Learning
• Introducing DRL
• Unity ML-Agents
• Agent and the Environment
• Understanding PPO
• Rewards and Reinforcement Learning
• Imitation and Transfer Learning
• Building Multi-Agent Environments
• Section 3: Building Games
• Debugging/Testing a Game with DRL
• Obstacle Tower Challenge and Beyond

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