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Learning to Learn
by Sebastian Thrun Lorien PrattOver the past three decades or so, research on machine learning and data mining has led to a wide variety of algorithms that learn general functions from experience. As machine learning is maturing, it has begun to make the successful transition from academic research to various practical applications. Generic techniques such as decision trees and artificial neural networks, for example, are now being used in various commercial and industrial applications. Learning to Learn is an exciting new research direction within machine learning. Similar to traditional machine-learning algorithms, the methods described in Learning to Learn induce general functions from experience. However, the book investigates algorithms that can change the way they generalize, i.e., practice the task of learning itself, and improve on it. To illustrate the utility of learning to learn, it is worthwhile comparing machine learning with human learning. Humans encounter a continual stream of learning tasks. They do not just learn concepts or motor skills, they also learn bias, i.e., they learn how to generalize. As a result, humans are often able to generalize correctly from extremely few examples - often just a single example suffices to teach us a new thing. A deeper understanding of computer programs that improve their ability to learn can have a large practical impact on the field of machine learning and beyond. In recent years, the field has made significant progress towards a theory of learning to learn along with practical new algorithms, some of which led to impressive results in real-world applications. Learning to Learn provides a survey of some of the most exciting new research approaches, written by leading researchers in the field. Its objective is to investigate the utility and feasibility of computer programs that can learn how to learn, both from a practical and a theoretical point of view.
Learning to Live in the Knowledge Society: IFIP 20th World Computer Congress, IFIP TC 3 ED-L2L Conference, September 7-10, 2008, Milano, Italy (IFIP Advances in Information and Communication Technology #Vol. 173)
by Michael Kendall Brian SamwaysED-L2L, Learning to Live in the Knowledge Society, is one of the co-located conferences of the 20th World Computer Congress (WCC2008). The event is organized under the auspices of IFIP (International Federation for Information Processing) and is to be held in Milan from 7th to 10th September 2008. ED-L2L is devoted to themes related to ICT for education in the knowledge society. It provides an international forum for professionals from all continents to discuss research and practice in ICT and education. The event brings together educators, researchers, policy makers, curriculum designers, teacher educators, members of academia, teachers and content producers. ED-L2L is organised by the IFIP Technical Committee 3, Education, with the support of the Institute for Educational Technology, part of the National Research Council of Italy. The Institute is devoted to the study of educational innovation brought about through the use of ICT. Submissions to ED-L2L are published in this conference book. The published papers are devoted to the published conference themes: Developing digital literacy for the knowledge society: information problem solving, creating, capturing and transferring knowledge, commitment to lifelong learning Teaching and learning in the knowledge society, playful and fun learning at home and in the school New models, processes and systems for formal and informal learning environments and organisations Developing a collective intelligence, learning together and sharing knowledge ICT issues in education - ethics, equality, inclusion and parental role Educating ICT professionals for the global knowledge society Managing the transition to the knowledge society
Learning to Play: Reinforcement Learning and Games
by Aske PlaatIn this textbook the author takes as inspiration recent breakthroughs in game playing to explain how and why deep reinforcement learning works. In particular he shows why two-person games of tactics and strategy fascinate scientists, programmers, and game enthusiasts and unite them in a common goal: to create artificial intelligence (AI). After an introduction to the core concepts, environment, and communities of intelligence and games, the book is organized into chapters on reinforcement learning, heuristic planning, adaptive sampling, function approximation, and self-play. The author takes a hands-on approach throughout, with Python code examples and exercises that help the reader understand how AI learns to play. He also supports the main text with detailed pointers to online machine learning frameworks, technical details for AlphaGo, notes on how to play and program Go and chess, and a comprehensive bibliography.The content is class-tested and suitable for advanced undergraduate and graduate courses on artificial intelligence and games. It's also appropriate for self-study by professionals engaged with applications of machine learning and with games development. Finally it's valuable for any reader engaged with the philosophical implications of artificial and general intelligence, games represent a modern Turing test of the power and limitations of AI.
Learning to Program in Pascal and Delphi (PDF)
by S. LangfieldThis book is designed to help students on the AQA 'AS' Level Computing course to learn the programming covered in Unit 1, and to enable the Unit 3 Practical Exercise to be tackled using either Pascal or Delphi.
Learning To Program In Python (PDF)
by P. M. HeathcoteThis book is a straightforward guide to the Python programming language and programming techniques. It covers all of the practical programming skills that may be required up to GCSE level and for those at AS Level with limited exposure to Python. It is suitable for both experienced programmers, students or individuals with very little or no programming experience in other languages. It teaches basic syntax and programming techniques, and introduces three inbuilt Python modules: Tkinter, used for building a graphical user interface, which is an option that some users may like to include in their project work. SQLite, which enables the creation and processing of a database from within a Python program. This provides an alternative to writing to a text file when data needs to be stored and retrieved. pdb, Python’s debugging module, which can be used to help find elusive logic errors.
Learning to Program in Visual Basic (PDF)
by Sylvia LangfieldThis book is a straightforward guide to the Visual Basic programming language and programming techniques. It covers all of the practical programming skills that may be required up to GCSE level and for those at AS Level with limited exposure to VB. It is suitable for both experienced programmers, students or individuals with very little or no programming experience in other languages.
Learning to Program the Object-oriented Way with C#
by Vinny Cahill Donal LaffertyC# is a modern, object-oriented language that enables programmers to quickly build a wide range of applications for the new Microsoft .NET platform, which provides tools and services that fully exploit both computing and communications. Learning to Program the Object-Oriented Way with C# presents an introductory guide to this hot topic. The authors use a practice-based approach supported by lots of examples of increasing complexity and frequent graded exercises, which are available online. -Introduces an approach to learning programming based on the use of object orientation from day one. -Includes many worked examples, the code and solution to which are available online. -The book is being technically reviewed and approved by Microsoft. -One of the first introductory textbooks on C# and object orientation - based on the final release version at the beginning of 2002. -Suitable for courses in introductory programming.
Learning to Program with MATLAB: Building GUI Tools
by Craig S. LentAuthor Craig Lent’s 1st edition of Learning to Program with MATLAB: Building GUI Tools teaches the core concepts of computer programming, such as arrays, loops, function, basic data structures, etc., using MATLAB. The text has a focus on the fundamentals of programming and builds up to an emphasis on GUI tools, covering text-based programs first, then programs that produce graphics. This creates a visual expression of the underlying mathematics of a problem or design.
Learning to Program with MATLAB: Building GUI Tools
by Craig S. LentLearning to Program with MATLAB Introductory text integrating science, mathematics, and engineering to give a basic understanding of the fundamentals of computer programming with MATLAB Learning to Program with MATLAB: Building GUI Tools, Second Edition serves as a compact introduction to computer programming using the MATLAB language, covering elements of both program and graphical user interface (GUI) design to enable readers to create computer programs just like the ones they are accustomed to interacting with. Rather than being encyclopedic in scope, the goal of the text is to describe what users will find most useful and point to other features. Descriptions and examples of some of the most useful functions are included throughout, particularly with regards to engineering and science applications. The work also includes updated videos and problem solutions on an instructor companion website. The first edition of Learning to Program with MATLAB employed the MATLAB graphical user interface design environment (GUIDE) to develop the GUI tools. The second edition is based on the new and improved App Designer program, which has supplanted GUIDE. This edition includes: Core concepts of computer programming using MATLAB, such as arrays, loops, functions, and basic data structures How to write your own MATLAB functions, covering topics such as local workspaces, multiple outputs, function files, and other functional forms The new string class and table class, some new features of function arguments, and re-written sections for building GUI tools with App Designer Syntax for graphics and App Designer features, plus examples demonstrating the new way to handle string information Starting with the basics and building up to an emphasis on GUI tools, Learning to Program with MATLAB is a comprehensive introduction to programming in a robust and multipurpose language, making it an ideal classroom resource for both students and instructors in related programs of study.
Learning to Program with MATLAB: Building GUI Tools
by Craig S. LentLearning to Program with MATLAB Introductory text integrating science, mathematics, and engineering to give a basic understanding of the fundamentals of computer programming with MATLAB Learning to Program with MATLAB: Building GUI Tools, Second Edition serves as a compact introduction to computer programming using the MATLAB language, covering elements of both program and graphical user interface (GUI) design to enable readers to create computer programs just like the ones they are accustomed to interacting with. Rather than being encyclopedic in scope, the goal of the text is to describe what users will find most useful and point to other features. Descriptions and examples of some of the most useful functions are included throughout, particularly with regards to engineering and science applications. The work also includes updated videos and problem solutions on an instructor companion website. The first edition of Learning to Program with MATLAB employed the MATLAB graphical user interface design environment (GUIDE) to develop the GUI tools. The second edition is based on the new and improved App Designer program, which has supplanted GUIDE. This edition includes: Core concepts of computer programming using MATLAB, such as arrays, loops, functions, and basic data structures How to write your own MATLAB functions, covering topics such as local workspaces, multiple outputs, function files, and other functional forms The new string class and table class, some new features of function arguments, and re-written sections for building GUI tools with App Designer Syntax for graphics and App Designer features, plus examples demonstrating the new way to handle string information Starting with the basics and building up to an emphasis on GUI tools, Learning to Program with MATLAB is a comprehensive introduction to programming in a robust and multipurpose language, making it an ideal classroom resource for both students and instructors in related programs of study.
Learning to Quantify (The Information Retrieval Series #47)
by Andrea Esuli Alessandro Fabris Alejandro Moreo Fabrizio SebastianiThis open access book provides an introduction and an overview of learning to quantify (a.k.a. “quantification”), i.e. the task of training estimators of class proportions in unlabeled data by means of supervised learning. In data science, learning to quantify is a task of its own related to classification yet different from it, since estimating class proportions by simply classifying all data and counting the labels assigned by the classifier is known to often return inaccurate (“biased”) class proportion estimates. The book introduces learning to quantify by looking at the supervised learning methods that can be used to perform it, at the evaluation measures and evaluation protocols that should be used for evaluating the quality of the returned predictions, at the numerous fields of human activity in which the use of quantification techniques may provide improved results with respect to the naive use of classification techniques, and at advanced topics in quantification research. The book is suitable to researchers, data scientists, or PhD students, who want to come up to speed with the state of the art in learning to quantify, but also to researchers wishing to apply data science technologies to fields of human activity (e.g., the social sciences, political science, epidemiology, market research) which focus on aggregate (“macro”) data rather than on individual (“micro”) data.
Learning to Rank for Information Retrieval
by Tie-Yan LiuDue to the fast growth of the Web and the difficulties in finding desired information, efficient and effective information retrieval systems have become more important than ever, and the search engine has become an essential tool for many people. The ranker, a central component in every search engine, is responsible for the matching between processed queries and indexed documents. Because of its central role, great attention has been paid to the research and development of ranking technologies. In addition, ranking is also pivotal for many other information retrieval applications, such as collaborative filtering, definition ranking, question answering, multimedia retrieval, text summarization, and online advertisement. Leveraging machine learning technologies in the ranking process has led to innovative and more effective ranking models, and eventually to a completely new research area called “learning to rank”. Liu first gives a comprehensive review of the major approaches to learning to rank. For each approach he presents the basic framework, with example algorithms, and he discusses its advantages and disadvantages. He continues with some recent advances in learning to rank that cannot be simply categorized into the three major approaches – these include relational ranking, query-dependent ranking, transfer ranking, and semisupervised ranking. His presentation is completed by several examples that apply these technologies to solve real information retrieval problems, and by theoretical discussions on guarantees for ranking performance. This book is written for researchers and graduate students in both information retrieval and machine learning. They will find here the only comprehensive description of the state of the art in a field that has driven the recent advances in search engine development.
Learning to Rank for Information Retrieval and Natural Language Processing (Synthesis Lectures on Human Language Technologies)
by Hang LiLearning to rank refers to machine learning techniques for training the model in a ranking task. Learning to rank is useful for many applications in information retrieval, natural language processing, and data mining. Intensive studies have been conducted on the problem recently and significant progress has been made. This lecture gives an introduction to the area including the fundamental problems, existing approaches, theories, applications, and future work. The author begins by showing that various ranking problems in information retrieval and natural language processing can be formalized as two basic ranking tasks, namely ranking creation (or simply ranking) and ranking aggregation. In ranking creation, given a request, one wants to generate a ranking list of offerings based on the features derived from the request and the offerings. In ranking aggregation, given a request, as well as a number of ranking lists of offerings, one wants to generate a new ranking list of the offerings. Ranking creation (or ranking) is the major problem in learning to rank. It is usually formalized as a supervised learning task. The author gives detailed explanations on learning for ranking creation and ranking aggregation, including training and testing, evaluation, feature creation, and major approaches. Many methods have been proposed for ranking creation. The methods can be categorized as the pointwise, pairwise, and listwise approaches according to the loss functions they employ. They can also be categorized according to the techniques they employ, such as the SVM based, Boosting SVM, Neural Network based approaches. The author also introduces some popular learning to rank methods in details. These include PRank, OC SVM, Ranking SVM, IR SVM, GBRank, RankNet, LambdaRank, ListNet & ListMLE, AdaRank, SVM MAP, SoftRank, Borda Count, Markov Chain, and CRanking. The author explains several example applications of learning to rank including web search, collaborative filtering, definition search, keyphrase extraction, query dependent summarization, and re-ranking in machine translation. A formulation of learning for ranking creation is given in the statistical learning framework. Ongoing and future research directions for learning to rank are also discussed. Table of Contents: Introduction / Learning for Ranking Creation / Learning for Ranking Aggregation / Methods of Learning to Rank / Applications of Learning to Rank / Theory of Learning to Rank / Ongoing and Future Work
Learning to Rank for Information Retrieval and Natural Language Processing, Second Edition (Synthesis Lectures on Human Language Technologies)
by Hang LiLearning to rank refers to machine learning techniques for training a model in a ranking task. Learning to rank is useful for many applications in information retrieval, natural language processing, and data mining. Intensive studies have been conducted on its problems recently, and significant progress has been made. This lecture gives an introduction to the area including the fundamental problems, major approaches, theories, applications, and future work. The author begins by showing that various ranking problems in information retrieval and natural language processing can be formalized as two basic ranking tasks, namely ranking creation (or simply ranking) and ranking aggregation. In ranking creation, given a request, one wants to generate a ranking list of offerings based on the features derived from the request and the offerings. In ranking aggregation, given a request, as well as a number of ranking lists of offerings, one wants to generate a new ranking list of the offerings. Ranking creation (or ranking) is the major problem in learning to rank. It is usually formalized as a supervised learning task. The author gives detailed explanations on learning for ranking creation and ranking aggregation, including training and testing, evaluation, feature creation, and major approaches. Many methods have been proposed for ranking creation. The methods can be categorized as the pointwise, pairwise, and listwise approaches according to the loss functions they employ. They can also be categorized according to the techniques they employ, such as the SVM based, Boosting based, and Neural Network based approaches. The author also introduces some popular learning to rank methods in details. These include: PRank, OC SVM, McRank, Ranking SVM, IR SVM, GBRank, RankNet, ListNet & ListMLE, AdaRank, SVM MAP, SoftRank, LambdaRank, LambdaMART, Borda Count, Markov Chain, and CRanking. The author explains several example applications of learning to rank including web search, collaborative filtering, definition search, keyphrase extraction, query dependent summarization, and re-ranking in machine translation. A formulation of learning for ranking creation is given in the statistical learning framework. Ongoing and future research directions for learning to rank are also discussed. Table of Contents: Learning to Rank / Learning for Ranking Creation / Learning for Ranking Aggregation / Methods of Learning to Rank / Applications of Learning to Rank / Theory of Learning to Rank / Ongoing and Future Work
Learning to Solve Complex Scientific Problems
by David H. JonassenProblem solving is implicit in the very nature of all science, and virtually all scientists are hired, retained, and rewarded for solving problems. Although the need for skilled problem solvers has never been greater, there is a growing disconnect between the need for problem solvers and the educational capacity to prepare them. Learning to Solve Complex Scientific Problems is an immensely useful read offering the insights of cognitive scientists, engineers and science educators who explain methods for helping students solve the complexities of everyday, scientific problems. Important features of this volume include discussions on:*how problems are represented by the problem solvers and how perception, attention, memory, and various forms of reasoning impact the management of information and the search for solutions;*how academics have applied lessons from cognitive science to better prepare students to solve complex scientific problems;*gender issues in science and engineering classrooms; and*questions to guide future problem-solving research. The innovative methods explored in this practical volume will be of significant value to science and engineering educators and researchers, as well as to instructional designers.
Learning to Solve Complex Scientific Problems
by David H. JonassenProblem solving is implicit in the very nature of all science, and virtually all scientists are hired, retained, and rewarded for solving problems. Although the need for skilled problem solvers has never been greater, there is a growing disconnect between the need for problem solvers and the educational capacity to prepare them. Learning to Solve Complex Scientific Problems is an immensely useful read offering the insights of cognitive scientists, engineers and science educators who explain methods for helping students solve the complexities of everyday, scientific problems. Important features of this volume include discussions on:*how problems are represented by the problem solvers and how perception, attention, memory, and various forms of reasoning impact the management of information and the search for solutions;*how academics have applied lessons from cognitive science to better prepare students to solve complex scientific problems;*gender issues in science and engineering classrooms; and*questions to guide future problem-solving research. The innovative methods explored in this practical volume will be of significant value to science and engineering educators and researchers, as well as to instructional designers.
Learning Together Online: Research on Asynchronous Learning Networks
by Starr Roxanne Hiltz Ricki GoldmanThis book is about the past and future of research on the effectiveness of learning networks (also known as "e-learning" or "online learning" or "Web-based learning"). Learning networks are groups of people using computer technology, communicating and collaborating online to build knowledge together. Over the past decade there has been an explosion not only of online courses, but also of studies on them. In Learning Together Online: Research on Asynchronous Learning Networks, leading researchers in the field use an integrated theoretical framework, which they call "Online Interaction Learning Theory," to organize what past research shows and where future research is going. It models the variables and processes that are important in determining the relative effectiveness of online learners working to reach a deeper level of understanding by interacting with each other and with the texts under investigation. Now that there have been hundreds of studies and thousands of courses offered online, what does the empirical evidence show? This book addresses the question directly by presenting what is known from research results about how to design and teach courses effectively online, ranging from the organizational context and characteristics of students to learning theories and research design methods. It also provides a research agenda for the next decade. Learning Together Online: Research on Asynchronous Learning Networks is both a textbook for graduate students and a professional reference for faculty teaching online, researchers conducting studies, and graduate students taking courses about learning technologies who need to know the state of the art of research in the area of online learning.
Learning Together Online: Research on Asynchronous Learning Networks
by Starr Roxanne Hiltz Ricki GoldmanThis book is about the past and future of research on the effectiveness of learning networks (also known as "e-learning" or "online learning" or "Web-based learning"). Learning networks are groups of people using computer technology, communicating and collaborating online to build knowledge together. Over the past decade there has been an explosion not only of online courses, but also of studies on them. In Learning Together Online: Research on Asynchronous Learning Networks, leading researchers in the field use an integrated theoretical framework, which they call "Online Interaction Learning Theory," to organize what past research shows and where future research is going. It models the variables and processes that are important in determining the relative effectiveness of online learners working to reach a deeper level of understanding by interacting with each other and with the texts under investigation. Now that there have been hundreds of studies and thousands of courses offered online, what does the empirical evidence show? This book addresses the question directly by presenting what is known from research results about how to design and teach courses effectively online, ranging from the organizational context and characteristics of students to learning theories and research design methods. It also provides a research agenda for the next decade. Learning Together Online: Research on Asynchronous Learning Networks is both a textbook for graduate students and a professional reference for faculty teaching online, researchers conducting studies, and graduate students taking courses about learning technologies who need to know the state of the art of research in the area of online learning.
Learning TypeScript 2.x Second Edition: Develop And Maintain Captivating Web Applications With Ease
by Remo H. JansenTypeScript is an open source and cross-platform statically typed superset of JavaScript that compiles to plain JavaScript and runs in any browser or host. This book is a step-by-step guide that will take you through the use and benefits of TypeScript with the help of practical examples.
Learning Underscore.js
by Alex PopExplore the Underscore.js library by example using a test-driven development approach About This Book • Understand and learn to apply functional programming principles using the built-in functions of Underscore.js • Leverage and reuse Underscore.js-based code to create code that targets client, server, or database contexts • Take Underscore.js further by reusing code between client and server and by learning about other closely related libraries Who This Book Is For If you are a developer with fundamental JavaScript knowledge and want to use modern JavaScript libraries to extend your functional programming skills, then Underscore.js is an important library you should be familiar with. What You Will Learn • Reference and call Underscore.js functions using a modern JavaScript development workflow • Apply Underscore.js to JavaScript arrays, objects, and functions • Take advantage of object-oriented or functional programming techniques with Underscore.js • Leverage Underscore.js to create code that targets client, server, or database contexts • Extend Underscore.js functionality with other closely related libraries • Reuse Underscore.js-based code between client and server applications • Prepare for the upcoming JavaScript standard ECMAScript 6 and support older browsers In Detail Underscore.js is one of the most popular modern JavaScript libraries used for functional programming. It can be used as a base for building complex JavaScript applications in a sustainable manner and for building other JavaScript libraries. It embraces functional programming principles but is not opinionated and can be used with imperative, object-oriented, functional, or other programming styles. This book explores how to use Underscore.js to power your code and understand modern JavaScript development concepts while applying a lightweight and efficient workflow to build applications. The book starts with an incremental Underscore.js introduction by exploring key JavaScript concepts. You will then explore the basic features of Underscore.js in action and establish a lightweight development workflow that allows the provided examples to be guided by tests. The book then covers the functionality of Underscore.js with in-depth examples and explanations for understanding and applying the Underscore.js API. You'll also learn how to use Underscore.js as a base for your own modules and libraries within an object-oriented or functional programming style, and will be able to explore Underscore.js use cases in different environments. Eventually, you'll learn about libraries that are closely related with Underscore.js, how to share code between client and server, and how to prepare for the upcoming JavaScript standard ECMAScript 6. Style and approach This book takes an example-driven approach to describing some of the essential JavaScript concepts and practices that are useful for building sustainable applications.
Learning Unity 2D Game Development by Example
by Venita PereiraIf you are interested in creating your very own 2D games from scratch, then this book will give you all the tools you need to succeed. Whether you are completely new to Unity or have used Unity before and would like to learn about the new 2D features of Unity, this book is for you.
Learning Unity Android Game Development
by Thomas FinneganIf you are an Android developer who wants to learn how to build games with Unity for the Android platform, then this book is ideal for you. Some prior knowledge of C# and JavaScript would be helpful.
Learning Unity iOS Game Development
by Kyle LangleyBuild exciting games with Unity on iOS and publish them on the App Store About This Book • Take advantage of Unity 5's new tools to create a fully interactive mobile game • Learn how to connect your iTunes developer account and use Unity 5 to communicate with it • Use your Macintosh computer to publish your game to the App Store Who This Book Is For This book is for iOS developers who want to learn how to build games with Unity for the iOS platform. Some prior experience in game development would be useful. What You Will Learn • Create your own iTunes Connect Developer account and create an app within it • Set up iTunes Game Center features in iTunes Connect so you can use them within Unity 5 • Construct a game using C# that allows users to interactively control the game character • Use Unity 5's editor window to create a custom editor tool specific for the game made in the book • Store and keep track of data so the player is able to collect in-game pick-ups that can be used to purchase in-game goods • Use all game features so the player is able to fully navigate menus between the front menu and in the game state • Make, test, and finally release builds so you can play on your device and then submit the game to Apple for review In Detail Over recent years, the market for mobile game development using Unity has grown multi-fold with an overwhelming 600 million gamers playing games developed using Unity engine. The newly launched Unity 5 offers a wide range of dedicated and powerful tools for iOS developers who intend to follow the basics and gradually elevate their skills to revolutionize the way they design and publish games for the App Store. From beginners, to those who are experienced making video games, this book goes through the steps of using Unity 5 to make a game from the ground up and setting the game up with iTunes Game Center features. The book begins with an introduction to setting up an iTunes Connect developer account, this will allow you to use Unity to its full potential with iOS. You will create a new app in iTunes Connect with the settings for Apple approval. You will learn, in detail, how to use Unity 5 and the programming language C# to make a fully interactive game that keeps track of player progress, Game Center Leaderboards, and Achievements, as well as displaying iAds and offering In-App purchases. Moving on, you'll discover how to create development and release builds, enabling you to test the game on your device before finally submitting the game for Apple's approval. By the end of the book, you will have a complete understanding of how iTunes and Unity can be used in combination to build and publish a fully interactive and reliable game to the App Store. Style and approach This is a step-by-step guide that covers the fundamentals of gaming and reveals the secrets of building and monetizing games for the iOS platform.
Learning Unity Physics
by K. Aava RaniIf you are familiar with the fundamentals of Physics and have basic experience of Unity game development, but have no knowledge of using the two together, then this book is for you.
Learning Unreal Engine Android Game Development
by Nitish MisraIf you are a game developer, designer, artist, or a beginner in the gaming industry and want to make Android games with Unreal Engine 4 efficiently, this book is ideal for you.