Author : Martin Varga
Publisher : Packt Publishing Ltd
Page : 430 pages
File Size : 30,66 MB
Release : 2014-09-10
Category : Computers
ISBN : 1783554118
If you are a beginner to AndEngine, or mobile game development in general, and you are looking for a simple way to start making games for Android, this book is for you. You should already know the basics of Java programming, but no previous game development experience is required.
Author : Martin Varga
Publisher :
Page : 286 pages
File Size : 12,83 MB
Release : 2014-09-10
Category : Computers
ISBN : 9781783985968
If you are a beginner to AndEngine, or mobile game development in general, and you are looking for a simple way to start making games for Android, this book is for you. You should already know the basics of Java programming, but no previous game development experience is required.
Author : Maya Posch
Publisher : Packt Publishing Ltd
Page : 279 pages
File Size : 10,73 MB
Release : 2015-09-28
Category : Computers
ISBN : 1783981156
Move beyond basic games and explore the limits of AndEngine About This Book Extend the basic AndEngine features without modifying any of AndEngine's code Understand advanced technologies and gain the skills to create the ultimate games in AndEngine Theory supported with practical examples to stimulate your imagination and creativity Who This Book Is For This book is aimed at developers who have gone through all the basic AndEngine tutorials and books, and are looking for something more. It's also very suitable for developers with knowledge of other game engines who are looking to develop with AndEngine. Knowledge of Java, C++ and Android development are a prerequisite for getting the most out of this book. What You Will Learn Extend AndEngine to use and render 3D models Integrate and use various physics engines with AndEngine Advanced animations and their implementation in AndEngine Lighting theory and its application for both 2D and 3D objects Using skeletal animation with AndEngine Use GLSL shaders with AndEngine for effects and anti-aliasing Add sounds and effects to AndEngine using both basic and 3D audio libraries Efficient network implementations with AndEngine for multi-players In Detail AndEngine is a popular and easy-to-use game framework, best suited for Android game development. After learning the basics of creating an Android game using AndEngine it's time you move beyond the basics to explore further. For this you need to understand the theory behind many of the technologies AndEngine uses. This book aims to provide all the skills and tools you need to learn more about Android game development using AndEngine. With this book you will get a quick overview of the basics of AndEngine and Android application development. From there, you will learn how to use 3D models in a 2D scene, render a visual representation of a scene's objects, and create interaction between these objects. You will explore frame-based animations and learn to use skeletal animations. As the book progresses, you will be guided through exploring all the relevant aspects of rendering graphics with OpenGL ES, generating audio using OpenSL ES and OpenAL, making the best use of Android's network API, implementing anti-aliasing algorithms, shaders, dynamic lighting and much more. With all this, you will be ready to enhance the look and feel of your game with its user interface, sound effects and background music. After an in-depth study of 2D and 3D worlds and multi-player implementations, you will be a master in AndEngine and Android game development. Style and approach This book takes an in-depth tour of the many aspects of Android game development with the use of AndEngine. Each topic is covered extensively to act both as a practical guide as well as a reference.
Author : Jayme Schroeder
Publisher : Packt Publishing Ltd
Page : 607 pages
File Size : 18,31 MB
Release : 2013-01-01
Category : Computers
ISBN : 1849518998
A Cookbook with wide range of recipes to allow you to learn game development with AndEngine quickly and efficiently. "AndEngine for Android Game Development Cookbook" is geared toward developers who are interested in working with the most up-to-date version of AndEngine, sporting the brand new GLES 2.0 branch. The book will be helpful for developers who are attempting to break into the mobile game market with plans to release fun and exciting games while eliminating a large portion of the learning curve that is otherwise inevitable when getting into AndEngine development. This book requires a working installation of eclipse and the required libraries, including AndEngine and its various extensions set up prior to working with the recipes.
Author : John B. Heywood
Publisher : McGraw-Hill Education
Page : 930 pages
File Size : 28,18 MB
Release : 1988
Category : Internal combustion engines
ISBN : 9780071004992
This text, by a leading authority in the field, presents a fundamental and factual development of the science and engineering underlying the design of combustion engines and turbines. An extensive illustration program supports the concepts and theories discussed.
Author : Edward F. Maurina
Publisher : CRC Press
Page : 444 pages
File Size : 49,11 MB
Release : 2008-05-09
Category : Computers
ISBN : 1439871124
Multiplayer Gaming and Engine Coding for the Torque Game Engine shows game programmers how to get the most out of the Torque Game Engine (TGE), which is an inexpensive professional game engine available from GarageGames. This book allows people to make multiplayer games with TGE and also tells them how to improve their games by modifying the engine
Author : Ethem Alpaydin
Publisher : MIT Press
Page : 639 pages
File Size : 47,27 MB
Release : 2014-08-22
Category : Computers
ISBN : 0262325756
A substantially revised third edition of a comprehensive textbook that covers a broad range of topics not often included in introductory texts. The goal of machine learning is to program computers to use example data or past experience to solve a given problem. Many successful applications of machine learning exist already, including systems that analyze past sales data to predict customer behavior, optimize robot behavior so that a task can be completed using minimum resources, and extract knowledge from bioinformatics data. Introduction to Machine Learning is a comprehensive textbook on the subject, covering a broad array of topics not usually included in introductory machine learning texts. Subjects include supervised learning; Bayesian decision theory; parametric, semi-parametric, and nonparametric methods; multivariate analysis; hidden Markov models; reinforcement learning; kernel machines; graphical models; Bayesian estimation; and statistical testing. Machine learning is rapidly becoming a skill that computer science students must master before graduation. The third edition of Introduction to Machine Learning reflects this shift, with added support for beginners, including selected solutions for exercises and additional example data sets (with code available online). Other substantial changes include discussions of outlier detection; ranking algorithms for perceptrons and support vector machines; matrix decomposition and spectral methods; distance estimation; new kernel algorithms; deep learning in multilayered perceptrons; and the nonparametric approach to Bayesian methods. All learning algorithms are explained so that students can easily move from the equations in the book to a computer program. The book can be used by both advanced undergraduates and graduate students. It will also be of interest to professionals who are concerned with the application of machine learning methods.
Author : Tom Coleman
Publisher :
Page : 288 pages
File Size : 47,49 MB
Release : 2003
Category : Weights and measures
ISBN :
Author : Michael Reynolds
Publisher :
Page : 352 pages
File Size : 20,76 MB
Release : 1896
Category : Locomotive engineers
ISBN :
Author : Ethem Alpaydin
Publisher : MIT Press
Page : 709 pages
File Size : 23,93 MB
Release : 2020-03-24
Category : Computers
ISBN : 0262358069
A substantially revised fourth edition of a comprehensive textbook, including new coverage of recent advances in deep learning and neural networks. The goal of machine learning is to program computers to use example data or past experience to solve a given problem. Machine learning underlies such exciting new technologies as self-driving cars, speech recognition, and translation applications. This substantially revised fourth edition of a comprehensive, widely used machine learning textbook offers new coverage of recent advances in the field in both theory and practice, including developments in deep learning and neural networks. The book covers a broad array of topics not usually included in introductory machine learning texts, including supervised learning, Bayesian decision theory, parametric methods, semiparametric methods, nonparametric methods, multivariate analysis, hidden Markov models, reinforcement learning, kernel machines, graphical models, Bayesian estimation, and statistical testing. The fourth edition offers a new chapter on deep learning that discusses training, regularizing, and structuring deep neural networks such as convolutional and generative adversarial networks; new material in the chapter on reinforcement learning that covers the use of deep networks, the policy gradient methods, and deep reinforcement learning; new material in the chapter on multilayer perceptrons on autoencoders and the word2vec network; and discussion of a popular method of dimensionality reduction, t-SNE. New appendixes offer background material on linear algebra and optimization. End-of-chapter exercises help readers to apply concepts learned. Introduction to Machine Learning can be used in courses for advanced undergraduate and graduate students and as a reference for professionals.
