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Practical simulations for machine learning
Paperback
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- Book Synopsis
- 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 engine Use a game engine to synthesize images for use as training data Create simulation environments designed for training deep reinforcement learning and imitation learning models Use and apply efficient general-purpose algorithms for simulation-based ML, such as proximal policy optimization Train a variety of ML models using different approaches Enable ML tools to work with industry-standard game development tools, using PyTorch, and the Unity ML-Agents and Perception Toolkits
- About The Author
- Dr. Paris Buttfield-Addison is cofounder of Secret Lab (https://www.secretlab.com.au and @TheSecretLab on Twitter), a game development studio based in beautiful Hobart, Australia. Secret Lab builds games and game development tools, including the multi-award winning ABC Play School iPad games, Night in the Woods, the Qantas airlines Joey Playbox games, and the Yarn Spinner narrative game framework. Paris formerly worked as mobile product manager for Meebo (acquired by Google), has a degree in medieval history, a PhD in Computing, and writes technical books on mobile and game development (more than 20 so far) for O'Reilly Media. Paris particularly enjoys game design, statistics, law, machine learning, and human-centred technology research. He can be found on Twitter at @parisba and online at http://paris.id.au.
- Product Details
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- ISBN
- 9781492089926
- Format
- Paperback
- Publisher
- O'Reilly, (21 June 2022)
- Number of Pages
- 331
- Weight
- 716 grams
- Language
- English
- Dimensions
- 233 x 178 x 28 mm
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