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Author: Paris Buttfield-Addison
Publisher: "O'Reilly Media, Inc."
ISBN: 1492089893
Category : Computers
Languages : en
Pages : 334
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Book Description
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
Author: Paris Buttfield-Addison
Publisher: "O'Reilly Media, Inc."
ISBN: 1492089893
Category : Computers
Languages : en
Pages : 334
Get Book Here
Book Description
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
Author: Michael R. Berthold
Publisher: Springer
ISBN: 9783030445836
Category : Computers
Languages : en
Pages : 588
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Book Description
This open access book constitutes the proceedings of the 18th International Conference on Intelligent Data Analysis, IDA 2020, held in Konstanz, Germany, in April 2020. The 45 full papers presented in this volume were carefully reviewed and selected from 114 submissions. Advancing Intelligent Data Analysis requires novel, potentially game-changing ideas. IDA’s mission is to promote ideas over performance: a solid motivation can be as convincing as exhaustive empirical evaluation.
Author: Allen B. Downey
Publisher: No Starch Press
ISBN: 1718502176
Category : Computers
Languages : en
Pages : 277
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Book Description
Modeling and Simulation in Python teaches readers how to analyze real-world scenarios using the Python programming language, requiring no more than a background in high school math. Modeling and Simulation in Python is a thorough but easy-to-follow introduction to physical modeling—that is, the art of describing and simulating real-world systems. Readers are guided through modeling things like world population growth, infectious disease, bungee jumping, baseball flight trajectories, celestial mechanics, and more while simultaneously developing a strong understanding of fundamental programming concepts like loops, vectors, and functions. Clear and concise, with a focus on learning by doing, the author spares the reader abstract, theoretical complexities and gets right to hands-on examples that show how to produce useful models and simulations.
Author: Zhang, Ming
Publisher: IGI Global
ISBN: 1466621761
Category : Computers
Languages : en
Pages : 455
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Book Description
"This book introduces Higher Order Neural Networks (HONNs) to computer scientists and computer engineers as an open box neural networks tool when compared to traditional artificial neural networks"--Provided by publisher.
Author: Shuyu Sun
Publisher: Gulf Professional Publishing
ISBN: 0128209623
Category : Science
Languages : en
Pages : 342
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Book Description
Reservoir Simulation: Machine Learning and Modeling helps the engineer step into the current and most popular advances in reservoir simulation, learning from current experiments and speeding up potential collaboration opportunities in research and technology. This reference explains common terminology, concepts, and equations through multiple figures and rigorous derivations, better preparing the engineer for the next step forward in a modeling project and avoid repeating existing progress. Well-designed exercises, case studies and numerical examples give the engineer a faster start on advancing their own cases. Both computational methods and engineering cases are explained, bridging the opportunities between computational science and petroleum engineering. This book delivers a critical reference for today's petroleum and reservoir engineer to optimize more complex developments. - Understand commonly used and recent progress on definitions, models, and solution methods used in reservoir simulation - World leading modeling and algorithms to study flow and transport behaviors in reservoirs, as well as the application of machine learning - Gain practical knowledge with hand-on trainings on modeling and simulation through well designed case studies and numerical examples.
Author: Thomas Witelski
Publisher: Springer
ISBN: 3319230425
Category : Mathematics
Languages : en
Pages : 309
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Book Description
This book presents mathematical modelling and the integrated process of formulating sets of equations to describe real-world problems. It describes methods for obtaining solutions of challenging differential equations stemming from problems in areas such as chemical reactions, population dynamics, mechanical systems, and fluid mechanics. Chapters 1 to 4 cover essential topics in ordinary differential equations, transport equations and the calculus of variations that are important for formulating models. Chapters 5 to 11 then develop more advanced techniques including similarity solutions, matched asymptotic expansions, multiple scale analysis, long-wave models, and fast/slow dynamical systems. Methods of Mathematical Modelling will be useful for advanced undergraduate or beginning graduate students in applied mathematics, engineering and other applied sciences.
Author: Lawrence E. Widman
Publisher:
ISBN:
Category : Computers
Languages : en
Pages : 586
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Book Description
This interdisciplinary approach to computer modeling addresses both traditional simulationists seeking the greater representational flexibility and ease of use that AI techniques offer, and computer scientists seeking the greater power and realism that rigorous simulation techniques can provide. First section reveals the theoretical underpinnings of AI and simulation. Second section describes application of simulation techniques to current problems in AI research. Third section discusses application of AI methods to simulation.
Author: Timon Rabczuk
Publisher: Springer Nature
ISBN: 3031366441
Category : Technology & Engineering
Languages : en
Pages : 456
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Book Description
Machine learning (ML) approaches have been extensively and successfully employed in various areas, like in economics, medical predictions, face recognition, credit card fraud detection, and spam filtering. There is clearly also the potential that ML techniques developed in Engineering and the Sciences will drastically increase the possibilities of analysis and accelerate the design to analysis time. With the use of ML techniques, coupled to conventional methods like finite element and digital twin technologies, new avenues of modeling and simulation can be opened but the potential of these ML techniques needs to still be fully harvested, with the methods developed and enhanced. The objective of this book is to provide an overview of ML in Engineering and the Sciences presenting fundamental theoretical ingredients with a focus on the next generation of computer modeling in Engineering and the Sciences in which the exciting aspects of machine learning are incorporated. The book is of value to any researcher and practitioner interested in research or applications of ML in the areas of scientific modeling and computer aided engineering.
Author: Tarek I. Zohdi
Publisher: Springer Nature
ISBN: 3031180534
Category : Technology & Engineering
Languages : en
Pages : 123
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Book Description
The COVID-19 pandemic that started in 2019-2020 has led to a gigantic increase in modeling and simulation of infectious diseases. There are numerous topics associated with this epoch-changing event, such as (a) disease propagation, (b) transmission, (c) decontamination, and (d) vaccines. This is an evolving field. The targeted objective of this book is to expose researchers to key topics in this area, in a very concise manner. The topics selected for discussion have evolved with the progression of the pandemic. Beyond the introductory chapter on basic mathematics, optimization, and machine learning, the book covers four themes in modeling and simulation infectious diseases, specifically: Part 1: Macroscale disease propagation, Part 2: Microscale disease transmission and ventilation system design, Part 3: Ultraviolet viral decontamination, and Part 4: Vaccine design and immune response. It is important to emphasize that the rapid speed at which the simulations operate makes the presented computational tools easily deployable as digital twins, i.e., digital replicas of complex systems that can be inexpensively and safely optimized in a virtual setting and then used in the physical world afterward, thus reducing the costs of experiments and also accelerating development of new technologies.
Author: Masoud Fakhimi
Publisher: Springer Nature
ISBN: 3031599993
Category :
Languages : en
Pages : 359
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Book Description
