Items related to Practical Simulations for Machine Learning: Using Synthetic...
- PublisherO'Reilly Media
- Publication date2022
- ISBN 10 1492089923
- ISBN 13 9781492089926
- BindingPaperback
- LanguageEnglish
- Edition number1
- Number of pages331
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Practical Simulations for Machine Learning : Using Synthetic Data for Ai
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Practical Simulations for Machine Learning: Using Synthetic Data for AI (Paperback or Softback)
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Practical Simulations for Machine Learning
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Practical Simulations for Machine Learning: Using Synthetic Data for AI
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O'Reilly Media (edition 1), 2022
ISBN 10: 1492089923
ISBN 13: 9781492089926
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Practical Simulations for Machine Learning: Using Synthetic Data for AI
Published by
O'Reilly Media (edition 1), 2022
ISBN 10: 1492089923
ISBN 13: 9781492089926
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Practical Simulations for Machine Learning (Paperback)
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ISBN 10: 1492089923
ISBN 13: 9781492089926
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Paperback. Condition: new. Paperback. 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" 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. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Seller Inventory # 9781492089926
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