Neural Network Programming with Java Second Edition

Neural Network Programming with Java   Second Edition
Author: Alan M. F. Souza,Fabio M. Soares
Publsiher: Unknown
Total Pages: 269
Release: 2017-02-28
Genre: Electronic Book
ISBN: 1787126056

Download Neural Network Programming with Java Second Edition Book in PDF, Epub and Kindle

Create and unleash the power of neural networks by implementing professional, clean, and clear Java codeAbout This Book* Learn to build amazing projects using neural networks including forecasting the weather and pattern recognition* Explore the Java multi-platform feature to run your personal neural networks everywhere* This step-by-step guide will help you solve real-world problems and links neural network theory to their applicationWho This Book Is ForThis book is for Java developers who want to know how to develop smarter applications using the power of neural networks. Those who deal with a lot of complex data and want to use it efficiently in their day-to-day apps will find this book quite useful. Some basic experience with statistical computations is expected.What You Will Learn* Develop an understanding of neural networks and how they can be fitted* Explore the learning process of neural networks* Build neural network applications with Java using hands-on examples* Discover the power of neural network's unsupervised learning process to extract the intrinsic knowledge hidden behind the data* Apply the code generated in practical examples, including weather forecasting and pattern recognition* Understand how to make the best choice of learning parameters to ensure you have a more effective application* Select and split data sets into training, test, and validation, and explore validation strategiesIn DetailWant to discover the current state-of-art in the field of neural networks that will let you understand and design new strategies to apply to more complex problems? This book takes you on a complete walkthrough of the process of developing basic to advanced practical examples based on neural networks with Java, giving you everything you need to stand out.You will first learn the basics of neural networks and their process of learning. We then focus on what Perceptrons are and their features. Next, you will implement self-organizing maps using practical examples. Further on, you will learn about some of the applications that are presented in this book such as weather forecasting, disease diagnosis, customer profiling, generalization, extreme machine learning, and characters recognition (OCR). Finally, you will learn methods to optimize and adapt neural networks in real time.All the examples generated in the book are provided in the form of illustrative source code, which merges object-oriented programming (OOP) concepts and neural network features to enhance your learning experience.

Introduction to Neural Networks with Java

Introduction to Neural Networks with Java
Author: Jeff Heaton
Publsiher: Heaton Research Incorporated
Total Pages: 380
Release: 2005
Genre: Computers
ISBN: 9780977320608

Download Introduction to Neural Networks with Java Book in PDF, Epub and Kindle

In addition to showing the programmer how to construct Neural Networks, the book discusses the Java Object Oriented Neural Engine (JOONE), a free open source Java neural engine. (Computers)

Deep Learning Practical Neural Networks with Java

Deep Learning  Practical Neural Networks with Java
Author: Yusuke Sugomori,Bostjan Kaluza,Fabio M. Soares,Alan M. F. Souza
Publsiher: Packt Publishing Ltd
Total Pages: 744
Release: 2017-06-08
Genre: Computers
ISBN: 9781788471718

Download Deep Learning Practical Neural Networks with Java Book in PDF, Epub and Kindle

Build and run intelligent applications by leveraging key Java machine learning libraries About This Book Develop a sound strategy to solve predictive modelling problems using the most popular machine learning Java libraries. Explore a broad variety of data processing, machine learning, and natural language processing through diagrams, source code, and real-world applications This step-by-step guide will help you solve real-world problems and links neural network theory to their application Who This Book Is For This course is intended for data scientists and Java developers who want to dive into the exciting world of deep learning. It will get you up and running quickly and provide you with the skills you need to successfully create, customize, and deploy machine learning applications in real life. What You Will Learn Get a practical deep dive into machine learning and deep learning algorithms Explore neural networks using some of the most popular Deep Learning frameworks Dive into Deep Belief Nets and Stacked Denoising Autoencoders algorithms Apply machine learning to fraud, anomaly, and outlier detection Experiment with deep learning concepts, algorithms, and the toolbox for deep learning Select and split data sets into training, test, and validation, and explore validation strategies Apply the code generated in practical examples, including weather forecasting and pattern recognition In Detail Machine learning applications are everywhere, from self-driving cars, spam detection, document search, and trading strategies, to speech recognitionStarting with an introduction to basic machine learning algorithms, this course takes you further into this vital world of stunning predictive insights and remarkable machine intelligence. This course helps you solve challenging problems in image processing, speech recognition, language modeling. You will discover how to detect anomalies and fraud, and ways to perform activity recognition, image recognition, and text. You will also work with examples such as weather forecasting, disease diagnosis, customer profiling, generalization, extreme machine learning and more. By the end of this course, you will have all the knowledge you need to perform deep learning on your system with varying complexity levels, to apply them to your daily work. The course provides you with highly practical content explaining deep learning with Java, from the following Packt books: Java Deep Learning Essentials Machine Learning in Java Neural Network Programming with Java, Second Edition Style and approach This course aims to create a smooth learning path that will teach you how to effectively use deep learning with Java with other de facto components to get the most out of it. Through this comprehensive course, you'll learn the basics of predictive modelling and progress to solve real-world problems and links neural network theory to their application

Introduction to Neural Networks with Java

Introduction to Neural Networks with Java
Author: Jeff Heaton
Publsiher: Heaton Research, Inc.
Total Pages: 440
Release: 2008
Genre: Computers
ISBN: 9781604390087

Download Introduction to Neural Networks with Java Book in PDF, Epub and Kindle

Introduction to Neural Networks in Java, Second Edition, introduces the Java programmer to the world of Neural Networks and Artificial Intelligence. Neural network architectures such as the feedforward, Hopfield, and Self Organizing Map networks are discussed. Training techniques such as Backpropagation, Genetic Algorithms and Simulated Annealing are also introduced. Practical examples are given for each neural network. Examples include the Traveling Salesman problem, handwriting recognition, financial prediction, game strategy, learning mathematical functions and special application to Internet bots. All Java source code can be downloaded online.

Java Deep Learning Projects

Java Deep Learning Projects
Author: Md. Rezaul Karim
Publsiher: Packt Publishing Ltd
Total Pages: 436
Release: 2018-06-29
Genre: Computers
ISBN: 9781788996525

Download Java Deep Learning Projects Book in PDF, Epub and Kindle

You will build full-fledged, deep learning applications with Java and different open-source libraries. Master numerical computing, deep learning, and the latest Java programming features to carry out complex advanced tasks. This book is filled with best practices/tips after every project to help you optimize your deep learning models with ease.

Principles Of Artificial Neural Networks 2nd Edition

Principles Of Artificial Neural Networks  2nd Edition
Author: Graupe Daniel
Publsiher: World Scientific
Total Pages: 320
Release: 2007-04-05
Genre: Neural networks (Computer science)
ISBN: 9789814475563

Download Principles Of Artificial Neural Networks 2nd Edition Book in PDF, Epub and Kindle

The book should serve as a text for a university graduate course or for an advanced undergraduate course on neural networks in engineering and computer science departments. It should also serve as a self-study course for engineers and computer scientists in the industry. Covering major neural network approaches and architectures with the theories, this text presents detailed case studies for each of the approaches, accompanied with complete computer codes and the corresponding computed results. The case studies are designed to allow easy comparison of network performance to illustrate strengths and weaknesses of the different networks.

Introduction to Neural Networks for C 2nd Edition

Introduction to Neural Networks for C   2nd Edition
Author: Jeff Heaton
Publsiher: Heaton Research Incorporated
Total Pages: 432
Release: 2008-10
Genre: Computers
ISBN: 1604390093

Download Introduction to Neural Networks for C 2nd Edition Book in PDF, Epub and Kindle

This resource introduces the C# programmer to the world of Neural Networks and Artificial Intelligence. Training techniques, such as backpropagation, genetic algorithms, and simulated annealing are also introduced.

The Nonlinear Workbook

The Nonlinear Workbook
Author: Willi-Hans Steeb
Publsiher: World Scientific Publishing Company
Total Pages: 640
Release: 2002-12-30
Genre: Electronic Book
ISBN: 9789813106093

Download The Nonlinear Workbook Book in PDF, Epub and Kindle

The study of nonlinear dynamical systems has advanced tremendously in the last 15 years, making a big impact on science and technology. This book provides all the techniques and methods used in nonlinear dynamics. The concepts and underlying mathematics are discussed in detail. The numerical and symbolic methods are implemented in C++, SymbolicC++ and Java. Object-oriented techniques are also applied. The book contains more than 100 ready-to-run programs. The text has also been designed for a one-year course at both the junior and senior levels in nonlinear dynamics. The topics discussed in the book are part of e-learning and distance learning courses conducted by the International School for Scientific Computing. Request Inspection Copy

Natural Language Processing with Java

Natural Language Processing with Java
Author: Richard M. Reese,AshishSingh Bhatia
Publsiher: Packt Publishing Ltd
Total Pages: 318
Release: 2018-07-31
Genre: Computers
ISBN: 9781788993067

Download Natural Language Processing with Java Book in PDF, Epub and Kindle

Explore various approaches to organize and extract useful text from unstructured data using Java Key Features Use deep learning and NLP techniques in Java to discover hidden insights in text Work with popular Java libraries such as CoreNLP, OpenNLP, and Mallet Explore machine translation, identifying parts of speech, and topic modeling Book Description Natural Language Processing (NLP) allows you to take any sentence and identify patterns, special names, company names, and more. The second edition of Natural Language Processing with Java teaches you how to perform language analysis with the help of Java libraries, while constantly gaining insights from the outcomes. You’ll start by understanding how NLP and its various concepts work. Having got to grips with the basics, you’ll explore important tools and libraries in Java for NLP, such as CoreNLP, OpenNLP, Neuroph, and Mallet. You’ll then start performing NLP on different inputs and tasks, such as tokenization, model training, parts-of-speech and parsing trees. You’ll learn about statistical machine translation, summarization, dialog systems, complex searches, supervised and unsupervised NLP, and more. By the end of this book, you’ll have learned more about NLP, neural networks, and various other trained models in Java for enhancing the performance of NLP applications. What you will learn Understand basic NLP tasks and how they relate to one another Discover and use the available tokenization engines Apply search techniques to find people, as well as things, within a document Construct solutions to identify parts of speech within sentences Use parsers to extract relationships between elements of a document Identify topics in a set of documents Explore topic modeling from a document Who this book is for Natural Language Processing with Java is for you if you are a data analyst, data scientist, or machine learning engineer who wants to extract information from a language using Java. Knowledge of Java programming is needed, while a basic understanding of statistics will be useful but not mandatory.

Principles of Artificial Neural Networks

Principles of Artificial Neural Networks
Author: Daniel Graupe
Publsiher: World Scientific
Total Pages: 500
Release: 2013-07-31
Genre: Computers
ISBN: 9789814522755

Download Principles of Artificial Neural Networks Book in PDF, Epub and Kindle

Artificial neural networks are most suitable for solving problems that are complex, ill-defined, highly nonlinear, of many and different variables, and/or stochastic. Such problems are abundant in medicine, in finance, in security and beyond. This volume covers the basic theory and architecture of the major artificial neural networks. Uniquely, it presents 18 complete case studies of applications of neural networks in various fields, ranging from cell-shape classification to micro-trading in finance and to constellation recognition — all with their respective source codes. These case studies demonstrate to the readers in detail how such case studies are designed and executed and how their specific results are obtained. The book is written for a one-semester graduate or senior-level undergraduate course on artificial neural networks. It is also intended to be a self-study and a reference text for scientists, engineers and for researchers in medicine, finance and data mining. Contents:Introduction and Role of Artificial Neural NetworksFundamentals of Biological Neural NetworksBasic Principles of ANNs and Their Early StructuresThe PerceptronThe MadalineBack PropagationHopfield NetworksCounter PropagationLarge Scale Memory Storage and Retrieval (LAMSTAR) NetworkAdaptive Resonance TheoryThe Cognitron and the NeocognitronStatistical TrainingRecurrent (Time Cycling) Back Propagation Networks Readership: Graduate and advanced senior students in artificial intelligence, pattern recognition & image analysis, neural networks, computational economics and finance, and biomedical engineering. Keywords:Neural Networks;Mathematical Derivations;Source Codes;Medical Applications;Data Mining;Cell-Shape Recognition;Micro-Trading

Encyclopedia of Information Science and Technology Second Edition

Encyclopedia of Information Science and Technology  Second Edition
Author: Khosrow-Pour, Mehdi
Publsiher: IGI Global
Total Pages: 5266
Release: 2008-10-31
Genre: Business & Economics
ISBN: 9781605660271

Download Encyclopedia of Information Science and Technology Second Edition Book in PDF, Epub and Kindle

"This set of books represents a detailed compendium of authoritative, research-based entries that define the contemporary state of knowledge on technology"--Provided by publisher.

The Nonlinear Workbook

The Nonlinear Workbook
Author: Willi-Hans Steeb
Publsiher: World Scientific
Total Pages: 621
Release: 2011
Genre: Science
ISBN: 9789814335775

Download The Nonlinear Workbook Book in PDF, Epub and Kindle

The Nonlinear Workbook provides a comprehensive treatment of all the techniques in nonlinear dynamics together with C++, Java and SymbolicC++ implementations. The book not only covers the theoretical aspects of the topics but also provides the practical tools. To understand the material, more than 100 worked out examples and 150 ready to run programs are included. New topics added to the fifth edition are Langton's ant, chaotic data communication, self-controlling feedback, differential forms and optimization, T-norms and T-conorms with applications.

Problems and Solutions in Scientific Computing with C and Java Simulations

Problems and Solutions in Scientific Computing with C   and Java Simulations
Author: Willi-Hans Steeb,Yorick Hardy,Alexandre Hardy,Ruedi Stoop
Publsiher: World Scientific Publishing Company
Total Pages: 432
Release: 2004-11-02
Genre: Mathematics
ISBN: 9789813102064

Download Problems and Solutions in Scientific Computing with C and Java Simulations Book in PDF, Epub and Kindle

Scientific computing is a collection of tools, techniques and theories required to develop and solve mathematical models in science and engineering on a computer. This timely book provides the various skills and techniques needed in scientific computing. The topics range in difficulty from elementary to advanced, and all the latest fields in scientific computing are covered such as matrices, numerical analysis, neural networks, genetic algorithms, etc. Presented in the format of problems and detailed solutions, important concepts and techniques are introduced and developed. Many problems include software simulations. Algorithms have detailed implementations in C++ or Java. This book will prove to be invaluable not only to students and research workers in the fields of scientific computing, but also to teachers of this subject who will find this text useful as a supplement. The topics discussed in this book are part of the e-learning and distance learning courses conducted by the International School of Scientific Computing, South Africa.

The Nonlinear Workbook

The Nonlinear Workbook
Author: Willi-Hans Steeb
Publsiher: World Scientific Publishing Company
Total Pages: 628
Release: 2008-06-17
Genre: Science
ISBN: 9789813107243

Download The Nonlinear Workbook Book in PDF, Epub and Kindle

The study of nonlinear dynamical systems has advanced tremendously in the last 20 years, making a big impact on science and technology. This book provides all the techniques and methods used in nonlinear dynamics. The concepts and underlying mathematics are discussed in detail. The numerical and symbolic methods are implemented in C++, SymbolicC++ and Java. Object-oriented techniques are also applied. The book contains more than 150 ready-to-run programs. The text has also been designed for a one-year course at both the junior and senior levels in nonlinear dynamics. The topics discussed in the book are part of e-learning and distance learning courses conducted by the International School for Scientific Computing, University of Johannesburg.

The Nonlinear Workbook

The Nonlinear Workbook
Author: Willi-Hans Steeb
Publsiher: World Scientific Publishing Company
Total Pages: 644
Release: 2011-03-16
Genre: Science
ISBN: 9789813100701

Download The Nonlinear Workbook Book in PDF, Epub and Kindle

The Nonlinear Workbook provides a comprehensive treatment of all the techniques in nonlinear dynamics together with C++, Java and SymbolicC++ implementations. The book not only covers the theoretical aspects of the topics but also provides the practical tools. To understand the material, more than 100 worked out examples and 150 ready to run programs are included. New topics added to the fifth edition are Langton's ant, chaotic data communication, self-controlling feedback, differential forms and optimization, T-norms and T-conorms with applications.