Practical Simulations for Machine Learning
Simulation and synthesis are core parts of the future of AI and machine learning. Consider: programmers, data scientists, and machine learning engineers can create the brain of a self-driving car without the car. Rather than use information from the real world, you can synthesize artificial data using simulations to train traditional machine learning models.That’s just the beginning.With this practical book, you’ll explore the possibilities of simulation- and synthesis-based machine learning and AI, concentrating on deep reinforcement learning and imitation learning techniques. AI and ML are increasingly data driven, and simulations are a powerful, engaging way to unlock their full potential.You'll learn how to:Design an approach for solving ML and AI problems using simulations with the Unity engineUse a game engine to synthesize images for use as training dataCreate simulation environments designed for training deep reinforcement learning and imitation learning modelsUse and apply efficient general-purpose algorithms for simulation-based ML, such as proximal policy optimizationTrain a variety of ML models using different approachesEnable ML tools to work with industry-standard game development tools, using PyTorch, and the Unity ML-Agents and Perception Toolkits
- 2022 Secret Lab.
Choosing a Book Format
EPUB is the standard publishing format used by many e-book readers including iBooks, Easy Reader, VoiceDream Reader, etc. This is the most popular and widely used format.
DAISY format is used by GoRead, Read2Go and most Kurzweil devices.
Audio (MP3) format is used by audio only devices, such as iPod.
Braille format is used by Braille output devices.
DAISY Audio format works on DAISY compatible players such as Victor Reader Stream.
Accessible Word format can be unzipped and opened in any tool that supports .docx files.