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Practical Simulations for Machine Learning : Using Synthetic Data for AI

Λεπτομέρειες βιβλιογραφικής εγγραφής
Τίτλος: Practical Simulations for Machine Learning : Using Synthetic Data for AI
Περιγραφή: 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
Συγγραφείς: Paris Buttfield-Addison, Mars Buttfield-Addison, Tim Nugent, Jon Manning
Resource Type: eBook.
Θέματα: Artificial intelligence--Computer simulation, Machine learning--Computer simulation
Categories: COMPUTERS / Data Science / Machine Learning, COMPUTERS / Artificial Intelligence / General, COMPUTERS / Computer Science, COMPUTERS / Machine Theory
Βάση Δεδομένων: eBook Index
FullText Text:
  Availability: 0
Header DbId: edsebk
DbLabel: eBook Index
An: 3304466
RelevancyScore: 962
AccessLevel: 6
PubType: eBook
PubTypeId: ebook
PreciseRelevancyScore: 962.24267578125
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  Data: Practical Simulations for Machine Learning : Using Synthetic Data for AI
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  Data: 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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RecordInfo BibRecord:
  BibEntity:
    Classifications:
      – Code: 006.31
        Scheme: ddc
        Type: prePub
    Languages:
      – Code: eng
        Text: English
    Subjects:
      – SubjectFull: Artificial intelligence--Computer simulation
        Type: general
      – SubjectFull: Machine learning--Computer simulation
        Type: general
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      – TitleFull: Practical Simulations for Machine Learning : Using Synthetic Data for AI
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            NameFull: Paris Buttfield-Addison
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            NameFull: Mars Buttfield-Addison
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            NameFull: Tim Nugent
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            NameFull: Jon Manning
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            NameFull: Paris Buttfield-Addison
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            NameFull: Mars Buttfield-Addison
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            NameFull: Tim Nugent
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            NameFull: Jon Manning
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          Dates:
            – D: 01
              M: 01
              Type: published
              Y: 2022
            – D: 03
              M: 08
              Type: profile
              Y: 2022
          Identifiers:
            – Type: isbn-print
              Value: 9781492089926
            – Type: isbn-electronic
              Value: 9781492089896
            – Type: isbn-electronic
              Value: 9781492089872
          Titles:
            – TitleFull: Practical Simulations for Machine Learning : Using Synthetic Data for AI
              Type: main
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