[PDF] Neural Networks In Unity - eBooks Review

Neural Networks In Unity


Neural Networks In Unity
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Neural Networks In Unity


Neural Networks In Unity
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Author : Abhishek Nandy
language : en
Publisher: Apress
Release Date : 2018-07-14

Neural Networks In Unity written by Abhishek Nandy and has been published by Apress this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-07-14 with Computers categories.


Learn the core concepts of neural networks and discover the different types of neural network, using Unity as your platform. In this book you will start by exploring back propagation and unsupervised neural networks with Unity and C#. You’ll then move onto activation functions, such as sigmoid functions, step functions, and so on. The author also explains all the variations of neural networks such as feed forward, recurrent, and radial. Once you’ve gained the basics, you’ll start programming Unity with C#. In this section the author discusses constructing neural networks for unsupervised learning, representing a neural network in terms of data structures in C#, and replicating a neural network in Unity as a simulation. Finally, you’ll define back propagation with Unity C#, before compiling your project. What You'll Learn Discover the concepts behind neural networks Work with Unity and C# See the difference between fully connected and convolutional neural networks Master neural network processing for Windows 10 UWP Who This Book Is For Gaming professionals, machine learning and deep learning enthusiasts.



Learn Unity Ml Agents Fundamentals Of Unity Machine Learning


Learn Unity Ml Agents Fundamentals Of Unity Machine Learning
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Author : Micheal Lanham
language : en
Publisher: Packt Publishing Ltd
Release Date : 2018-06-30

Learn Unity Ml Agents Fundamentals Of Unity Machine Learning written by Micheal Lanham and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-06-30 with Computers categories.


Transform games into environments using machine learning and Deep learning with Tensorflow, Keras, and Unity Key Features Learn how to apply core machine learning concepts to your games with Unity Learn the Fundamentals of Reinforcement Learning and Q-Learning and apply them to your games Learn How to build multiple asynchronous agents and run them in a training scenario Book Description Unity Machine Learning agents allow researchers and developers to create games and simulations using the Unity Editor, which serves as an environment where intelligent agents can be trained with machine learning methods through a simple-to-use Python API. This book takes you from the basics of Reinforcement and Q Learning to building Deep Recurrent Q-Network agents that cooperate or compete in a multi-agent ecosystem. You will start with the basics of Reinforcement Learning and how to apply it to problems. Then you will learn how to build self-learning advanced neural networks with Python and Keras/TensorFlow. From there you move o n to more advanced training scenarios where you will learn further innovative ways to train your network with A3C, imitation, and curriculum learning models. By the end of the book, you will have learned how to build more complex environments by building a cooperative and competitive multi-agent ecosystem. What you will learn Develop Reinforcement and Deep Reinforcement Learning for games. Understand complex and advanced concepts of reinforcement learning and neural networks Explore various training strategies for cooperative and competitive agent development Adapt the basic script components of Academy, Agent, and Brain to be used with Q Learning. Enhance the Q Learning model with improved training strategies such as Greedy-Epsilon exploration Implement a simple NN with Keras and use it as an external brain in Unity Understand how to add LTSM blocks to an existing DQN Build multiple asynchronous agents and run them in a training scenario Who this book is for This book is intended for developers with an interest in using Machine learning algorithms to develop better games and simulations with Unity. The reader will be required to have a working knowledge of C# and a basic understanding of Python.



Complex Valued Neural Networks


Complex Valued Neural Networks
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Author : Akira Hirose
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-03-23

Complex Valued Neural Networks written by Akira Hirose and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-03-23 with Computers categories.


This book is the second enlarged and revised edition of the first successful monograph on complex-valued neural networks (CVNNs) published in 2006, which lends itself to graduate and undergraduate courses in electrical engineering, informatics, control engineering, mechanics, robotics, bioengineering, and other relevant fields. In the second edition the recent trends in CVNNs research are included, resulting in e.g. almost a doubled number of references. The parametron invented in 1954 is also referred to with discussion on analogy and disparity. Also various additional arguments on the advantages of the complex-valued neural networks enhancing the difference to real-valued neural networks are given in various sections. The book is useful for those beginning their studies, for instance, in adaptive signal processing for highly functional sensing and imaging, control in unknown and changing environment, robotics inspired by human neural systems, and brain-like information processing, as well as interdisciplinary studies to realize comfortable society. It is also helpful to those who carry out research and development regarding new products and services at companies. The author wrote this book hoping in particular that it provides the readers with meaningful hints to make good use of neural networks in fully practical applications. The book emphasizes basic ideas and ways of thinking. Why do we need to consider neural networks that deal with complex numbers? What advantages do the complex-valued neural networks have? What is the origin of the advantages? In what areas do they develop principal applications? This book answers these questions by describing details and examples, which will inspire the readers with new ideas. The book is useful for those beginning their studies, for instance, in adaptive signal processing for highly functional sensing and imaging, control in unknown and changing environment, robotics inspired by human neural systems, and brain-like information processing, as well as interdisciplinary studies to realize comfortable society. It is also helpful to those who carry out research and development regarding new products and services at companies. The author wrote this book hoping in particular that it provides the readers with meaningful hints to make good use of neural networks in fully practical applications. The book emphasizes basic ideas and ways of thinking. Why do we need to consider neural networks that deal with complex numbers? What advantages do the complex-valued neural networks have? What is the origin of the advantages? In what areas do they develop principal applications? This book answers these questions by describing details and examples, which will inspire the readers with new ideas.



Learn Unity For 2d Game Development


Learn Unity For 2d Game Development
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Author : Alan Thorn
language : en
Publisher: Apress
Release Date : 2013-10-25

Learn Unity For 2d Game Development written by Alan Thorn and has been published by Apress this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-10-25 with Computers categories.


2D games are everywhere, from mobile devices and websites to game consoles and PCs. Timeless and popular, 2D games represent a substantial segment of the games market. In Learn Unity for 2D Game Development, targeted at both game development newcomers and established developers, experienced game developer Alan Thorn shows you how to use the powerful Unity engine to create fun and imaginative 2D games. Written in clear and accessible language, Learn Unity for 2D Game Development will show you how to set up a step-by-step 2D workflow in Unity, how to build and import textures, how to configure and work with cameras, how to establish pixel-perfect ratios, and all of this so you can put that infrastructure to work in a real, playable game. Then the final chapters show you how to put what you've already made to work in creating a card-matching game, plus you'll learn how to optimize your game for mobile devices.



Ai For Game Developers


Ai For Game Developers
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Author : David M. Bourg
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2004

Ai For Game Developers written by David M. Bourg and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2004 with Computers categories.


From the author of "Physics for Game Developers," comes a new, non-threatening introduction to the complex subject of game programming.



An Introduction To Neural Networks


An Introduction To Neural Networks
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Author : Kevin Gurney
language : en
Publisher: CRC Press
Release Date : 2018-10-08

An Introduction To Neural Networks written by Kevin Gurney and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-10-08 with Computers categories.


Though mathematical ideas underpin the study of neural networks, the author presents the fundamentals without the full mathematical apparatus. All aspects of the field are tackled, including artificial neurons as models of their real counterparts; the geometry of network action in pattern space; gradient descent methods, including back-propagation; associative memory and Hopfield nets; and self-organization and feature maps. The traditionally difficult topic of adaptive resonance theory is clarified within a hierarchical description of its operation. The book also includes several real-world examples to provide a concrete focus. This should enhance its appeal to those involved in the design, construction and management of networks in commercial environments and who wish to improve their understanding of network simulator packages. As a comprehensive and highly accessible introduction to one of the most important topics in cognitive and computer science, this volume should interest a wide range of readers, both students and professionals, in cognitive science, psychology, computer science and electrical engineering.



Neural Networks In The Analysis And Design Of Structures


Neural Networks In The Analysis And Design Of Structures
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Author : Zenon Waszczysznk
language : en
Publisher: Springer
Release Date : 2014-05-04

Neural Networks In The Analysis And Design Of Structures written by Zenon Waszczysznk and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-05-04 with Computers categories.


Neural Networks are a new, interdisciplinary tool for information processing. Neurocomputing being successfully introduced to structural problems which are difficult or even impossible to be analysed by standard computers (hard computing). The book is devoted to foundations and applications of NNs in the structural mechanics and design of structures.



Artificial Intelligence For Humans


Artificial Intelligence For Humans
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Author : Jeff Heaton
language : en
Publisher: Createspace Independent Publishing Platform
Release Date : 2013

Artificial Intelligence For Humans written by Jeff Heaton and has been published by Createspace Independent Publishing Platform this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013 with Algorithms categories.


« Artifical Intelligence for Humans is a book series meant to teach AI to those readers who lack an extensive mathematical background. The reader only needs knowledge of basic college algebra and computer programming. Additional topics are thoroughly explained. Every chapter also includes a programming example. Examples are currently provided in Java, C#, and Python. Other languages are planned. »--



The Principles Of Deep Learning Theory


The Principles Of Deep Learning Theory
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Author : Daniel A. Roberts
language : en
Publisher: Cambridge University Press
Release Date : 2022-05-26

The Principles Of Deep Learning Theory written by Daniel A. Roberts and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-05-26 with Computers categories.


This volume develops an effective theory approach to understanding deep neural networks of practical relevance.



Advances In Visual Computing


Advances In Visual Computing
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Author : George Bebis
language : en
Publisher: Springer Nature
Release Date : 2023-11-30

Advances In Visual Computing written by George Bebis and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-11-30 with Computers categories.


This volume LNCS 14361 and 14362 constitutes the refereed proceedings of the, 16th International Symposium, ISVC 2023, in October 2023, held at Lake Tahoe, NV, USA. The 42 full papers and 13 poster papers were carefully reviewed and selected from 120 submissions. A total of 25 papers were also accepted for oral presentation in special tracks from 34 submissions. The following topical sections followed as: Part 1: ST: Biomedical Image Analysis Techniques for Cancer Detection, Diagnosis and Management; Visualization; Video Analysis and Event Recognition; ST: Innovations in Computer Vision & Machine Learning for Critical & Civil Infrastructures; ST: Generalization in Visual Machine Learning; Computer Graphics; Medical Image Analysis; Biometrics; Autonomous Anomaly Detection in Images; ST: Artificial Intelligence in Aerial and Orbital Imagery; ST: Data Gathering, Curation, and Generation for Computer Vision and Robotics in Precision Agriculture. Part 2: Virtual Reality; Segmentation; Applications; Object Detection and Recognition; Deep Learning; Poster.