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Practical Artificial Intelligence with Swift : From Fundamental Theory to Development of AI-Driven Apps
Published by O'Reilly Media, Incorporated, 2019
ISBN 10: 1492044814 ISBN 13: 9781492044819
Language: English
Condition: Very Good. Former library book; may include library markings. Used book that is in excellent condition. May show signs of wear or have minor defects.
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Practical Artificial Intelligence with Swift: From Fundamental Theory to Development of AI-Driven Apps
Seller: Bay State Book Company, North Smithfield, RI, U.S.A.
Seller rating 5 out of 5 stars
Condition: good. The book is in good condition with all pages and cover intact, including the dust jacket if originally issued. The spine may show light wear. Pages may contain some notes or highlighting, and there might be a "From the library of" label. Boxed set packaging, shrink wrap, or included media like CDs may be missing.
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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
Language: English
Paperback. Condition: Very Good. 1. It's a well-cared-for item that has seen limited use. The item may show minor signs of wear. All the text is legible, with all pages included. It may have slight markings and/or highlighting.
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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
Language: English
Paperback. Condition: Fair. 1. The item might be beaten up but readable. May contain markings or highlighting, as well as stains, bent corners, or any other major defect, but the text is not obscured in any way.
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paperback. Condition: Good. Connecting readers with great books since 1972! Used textbooks may not include companion materials such as access codes, etc. May have some wear or writing/highlighting. We ship orders daily and Customer Service is our top priority!
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Paperback. Condition: New. Create and implement AI-based features in your Swift apps for iOS, macOS, tvOS, and watchOS. With this practical book, programmers and developers of all kinds will find a one-stop shop for AI and machine learning with Swift. Taking a task-based approach, you'll learn how to build features that use powerful AI features to identify images, make predictions, generate content, recommend things, and more.AI is increasingly essential for every developer-and you don't need to be a data scientist or mathematician to take advantage of it in your apps. Explore Swift-based AI and ML techniques for building applications. Learn where and how AI-driven features make sense. Inspect tools such as Apple's Python-powered Turi Create and Google's Swift for TensorFlow to train and build models.I: Fundamentals and Tools-Learn AI basics, our task-based approach, and discover how to build or find a dataset.II: Task Based AI-Build vision, audio, text, motion, and augmentation-related features; learn how to convert preexisting models.III: Beyond-Discover the theory behind task-based practice, explore AI and ML methods, and learn how you can build it all from scratch. if you want to.
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Condition: New.
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Paperback. Condition: New. 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.
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Practical Simulations for Machine Learning : Using Synthetic Data for Ai
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
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Practical Artificial Intelligence With Swift : From Fundamental Theory to Development of AI-Driven Apps
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
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Practical Artificial Intelligence With Swift : From Fundamental Theory to Development of AI-Driven Apps
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Add to basketSoft cover. Condition: New. 1st Edition. 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.
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Practical Simulations for Machine Learning : Using Synthetic Data for Ai
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
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Practical Artificial Intelligence with Swift
Seller: Rarewaves.com USA, London, LONDO, United Kingdom
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Add to basketPaperback. Condition: New. Create and implement AI-based features in your Swift apps for iOS, macOS, tvOS, and watchOS. With this practical book, programmers and developers of all kinds will find a one-stop shop for AI and machine learning with Swift. Taking a task-based approach, you'll learn how to build features that use powerful AI features to identify images, make predictions, generate content, recommend things, and more.AI is increasingly essential for every developer-and you don't need to be a data scientist or mathematician to take advantage of it in your apps. Explore Swift-based AI and ML techniques for building applications. Learn where and how AI-driven features make sense. Inspect tools such as Apple's Python-powered Turi Create and Google's Swift for TensorFlow to train and build models.I: Fundamentals and Tools-Learn AI basics, our task-based approach, and discover how to build or find a dataset.II: Task Based AI-Build vision, audio, text, motion, and augmentation-related features; learn how to convert preexisting models.III: Beyond-Discover the theory behind task-based practice, explore AI and ML methods, and learn how you can build it all from scratch. if you want to.
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Practical Simulations for Machine Learning
Seller: Rarewaves.com USA, London, LONDO, United Kingdom
Seller rating 5 out of 5 stars
US$ 79.92
Convert currencyFree shipping from United Kingdom to U.S.A.Quantity: 6 available
Add to basketPaperback. Condition: New. 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.
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Practical Artificial Intelligence with Swift: From Fundamental Theory to Development of AI-Driven Apps
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Practical Artificial Intelligence With Swift: From Fundamental Theory to Development of Ai-driven Apps
Published by Oreilly & Associates Inc, 2019
ISBN 10: 1492044814 ISBN 13: 9781492044819
Language: English
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Add to basketPaperback. Condition: Brand New. 501 pages. 9.25x7.00x1.00 inches. In Stock.
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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
Published by Oreilly & Associates Inc, 2022
ISBN 10: 1492089923 ISBN 13: 9781492089926
Language: English
US$ 75.70
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Add to basketPaperback. Condition: Brand New. 500 pages. 9.19x7.00x0.91 inches. In Stock.
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Condition: New. pp. 526.
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Condition: New. 1st edition NO-PA16APR2015-KAP.
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Add to basketPaperback. Condition: New. Create and implement AI-based features in your Swift apps for iOS, macOS, tvOS, and watchOS. With this practical book, programmers and developers of all kinds will find a one-stop shop for AI and machine learning with Swift. Taking a task-based approach, you'll learn how to build features that use powerful AI features to identify images, make predictions, generate content, recommend things, and more.AI is increasingly essential for every developer-and you don't need to be a data scientist or mathematician to take advantage of it in your apps. Explore Swift-based AI and ML techniques for building applications. Learn where and how AI-driven features make sense. Inspect tools such as Apple's Python-powered Turi Create and Google's Swift for TensorFlow to train and build models.I: Fundamentals and Tools-Learn AI basics, our task-based approach, and discover how to build or find a dataset.II: Task Based AI-Build vision, audio, text, motion, and augmentation-related features; learn how to convert preexisting models.III: Beyond-Discover the theory behind task-based practice, explore AI and ML methods, and learn how you can build it all from scratch. if you want to.
