Neural Network Programming With Java

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Neural Network Programming With Java

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Author : David V.
language : en
Publisher: Createspace Independent Publishing Platform
Release Date : 2017-02-28

Neural Network Programming With Java written by David V. 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 2017-02-28 with categories.

This book is an exploration of neural networks and how to implement them in Java. First, the reader is guided so as to understand what neural networks are. You will learn how they operate. The process of learning in neural networks is very important. This is the concept which makes neural networks behave in the same manner as the brain of human beings. This process is discussed in this book. You are also guided on how to implement this in Java. The Java lego robots are very common in the field of artificial intelligence. This book guides you on how to implement these in Java. Recurrent neural networks, which are believed to have memory, are discussed in detail. These work in such a way that the value will be calculated based on the value obtained in the previous step. You will learn how to implement such a network in Java. Convolutional neural networks are also explored in detail. You will learn how these work as well as how to implement them in Java. The following topics are discussed in this book: -Understanding Neural Networks -Learning in Neural Networks -Java Lego Robots Neural Network -Convolutional Neural Networks -Recurrent Neural Networks

Neural Network Programming With Java

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Author : Alan Souza
language : en
Publisher: Packt Publishing
Release Date : 2016-01-13

Neural Network Programming With Java written by Alan Souza and has been published by Packt Publishing this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-01-13 with Computers categories.

Create and unleash the power of neural networks by implementing professional 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 with basic Java programming knowledge. No previous knowledge of neural networks is required as this book covers the concepts from scratch.What You Will Learn• Get to grips with the basics of neural networks and what they are used for• Develop neural networks using hands-on examples• Explore and code the most widely-used learning algorithms to make your neural network learn from most types of data• 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 strategies• Discover how to improve and optimize your neural networkIn DetailVast quantities of data are produced every second. In this context, neural networks become a powerful technique to extract useful knowledge from large amounts of raw, seemingly unrelated data. One of the most preferred languages for neural network programming is Java as it is easier to write code using it, and most of the most popular neural network packages around already exist for Java. This makes it a versatile programming language for neural networks.This book gives you a complete walkthrough of the process of developing basic to advanced practical examples based on neural networks with Java.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 the concepts you've learned. Furthermore, you will learn about some of the applications that are presented in this book such as weather forecasting, disease diagnosis, customer profiling, 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.Style and approachThis book adopts a step-by-step approach to neural network development and provides many hands-on examples using Java programming. Each neural network concept is explored through real-world problems and is delivered in an easy-to-comprehend manner.

Neural Network Programming With Java Second Edition

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Author : Alan M. F. Souza
language : en
Publisher:
Release Date : 2017-02-28

Neural Network Programming With Java Second Edition written by Alan M. F. Souza and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-02-28 with categories.

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.

Deep Learning Practical Neural Networks With Java

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Author : Yusuke Sugomori
language : en
Publisher: Packt Publishing Ltd
Release Date : 2017-06-08

Deep Learning Practical Neural Networks With Java written by Yusuke Sugomori 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 2017-06-08 with Computers categories.

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

Java Deep Learning Cookbook

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Author : Rahul Raj
language : en
Publisher: Packt Publishing Ltd
Release Date : 2019-11-08

Java Deep Learning Cookbook written by Rahul Raj 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 2019-11-08 with Computers categories.

Use Java and Deeplearning4j to build robust, scalable, and highly accurate AI models from scratch Key FeaturesInstall and configure Deeplearning4j to implement deep learning models from scratchExplore recipes for developing, training, and fine-tuning your neural network models in JavaModel neural networks using datasets containing images, text, and time-series dataBook Description Java is one of the most widely used programming languages in the world. With this book, you will see how to perform deep learning using Deeplearning4j (DL4J) – the most popular Java library for training neural networks efficiently. This book starts by showing you how to install and configure Java and DL4J on your system. You will then gain insights into deep learning basics and use your knowledge to create a deep neural network for binary classification from scratch. As you progress, you will discover how to build a convolutional neural network (CNN) in DL4J, and understand how to construct numeric vectors from text. This deep learning book will also guide you through performing anomaly detection on unsupervised data and help you set up neural networks in distributed systems effectively. In addition to this, you will learn how to import models from Keras and change the configuration in a pre-trained DL4J model. Finally, you will explore benchmarking in DL4J and optimize neural networks for optimal results. By the end of this book, you will have a clear understanding of how you can use DL4J to build robust deep learning applications in Java. What you will learnPerform data normalization and wrangling using DL4JBuild deep neural networks using DL4JImplement CNNs to solve image classification problemsTrain autoencoders to solve anomaly detection problems using DL4JPerform benchmarking and optimization to improve your model's performanceImplement reinforcement learning for real-world use cases using RL4JLeverage the capabilities of DL4J in distributed systemsWho this book is for If you are a data scientist, machine learning developer, or a deep learning enthusiast who wants to implement deep learning models in Java, this book is for you. Basic understanding of Java programming as well as some experience with machine learning and neural networks is required to get the most out of this book.

Neural Network Programming With Python

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Author : Fabio M. Soares
language : en
Publisher:
Release Date : 2017-04-28

Neural Network Programming With Python written by Fabio M. Soares and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-04-28 with categories.

Build smarter programs with the power of neural networks and the simplicity of PythonAbout This Book* Make your roots stronger in neural networks by this concept-rich yet highly practical guide; from single layer to multiple layers with the help of Python* Through this book, you will develop a strong background in neural networks, regardless of your level of previous knowledge in this subject* You will be able to implement solutions from scratch, so the whole process on foundations of neural network solution design will be paced by youWho This Book Is ForThis book is designed for novices as well as intermediate Python developers who have a statistical background and want to work with neural networks to get better results from complex data. It also contains enough food for thought for those who want to improve their skills in machine learning and deep learning.What You Will Learn* See the latest innovations in the field* Become fluent in Python to develop neural networks solutions capable of solving complex and interesting tasks* Implement neural networks step-by-step* Solve your complex computational problems with the aid of neural networks and Python* The reader will be able to set up his/her neural network with ease, according to the objective he/she wants to apply.* The reader will be able to design time series based models using RNNs in Python.* Will be able to design high level solutions with CNNs in PythonIn DetailIf you wish to solve your complex computational problem efficiently, neural networks come to the rescue. This book will teach you how to ace neural networks and solve your computational problems with Python-right from predicting to self-learning models-with ease. We start off with neural network design, then you'll build a solid foundational knowledge of how a neural network learns from data, and the principles behind it.This book cover various types of neural networks including recurrent neural networks and convoluted neural networks. You will not only learn how to train neural networks, but also see a generalization of these networks. With the help of practical examples and real-world use cases, you will learn to implement these neural networks in your applications.

Artificial Neural Networks With Java

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Author : Igor Livshin
language : en
Publisher:
Release Date : 2022

Artificial Neural Networks With Java written by Igor Livshin and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022 with categories.

Develop neural network applications using the Java environment. After learning the rules involved in neural network processing, this second edition shows you how to manually process your first neural network example. The book covers the internals of front and back propagation and helps you understand the main principles of neural network processing. You also will learn how to prepare the data to be used in neural network development and you will be able to suggest various techniques of data preparation for many unconventional tasks. This book discusses the practical aspects of using Java for neural network processing. You will know how to use the Encog Java framework for processing large-scale neural network applications. Also covered is the use of neural networks for approximation of non-continuous functions. In addition to using neural networks for regression, this second edition shows you how to use neural networks for computer vision. It focuses on image recognition such as the classification of handwritten digits, input data preparation and conversion, and building the conversion program. And you will learn about topics related to the classification of handwritten digits such as network architecture, program code, programming logic, and execution. The step-by-step approach taken in the book includes plenty of examples, diagrams, and screenshots to help you grasp the concepts quickly and easily. What You Will Learn Use Java for the development of neural network applications Prepare data for many different tasks Carry out some unusual neural network processing Use a neural network to process non-continuous functions Develop a program that recognizes handwritten digits.

Build A Computer From Scratch

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Author : Jeff Heaton
language : en
Publisher: Heaton Research, Inc.
Release Date : 2006-06

Build A Computer From Scratch written by Jeff Heaton and has been published by Heaton Research, Inc. this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006-06 with Computers categories.

Building a computer system lets users get exactly the computer system that they need. This book takes them through all of the steps to create a powerful computer system. Includes 120+ photographs to guide readers through the process. (Computer Books)

Programming Neural Networks With Encog 3 In Java

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Author : Jeff Heaton
language : en
Publisher:
Release Date : 2011

Programming Neural Networks With Encog 3 In Java written by Jeff Heaton and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011 with Computers categories.

Beginning where our introductory neural network programing book left off, this book introduces you to Encog. Encog allows you to focus less on the actual implementation of neural networks and focus on how to use them. Encog is an advanced neural network programming framework that allows you to create a variety of neural network architectures using the Java programming language. Neural network architectures such as feedforward/perceptrons, Hopfield, Elman, Jordan, Radial Basis Function, and Self Organizing maps are all demonstrated. This book also shows how to use Encog to train neural networks using a variety of means. Several propagation techniques, such as back propagation, resilient propagation (RPROP) and the Manhattan update rule are discussed. Additionally, training with a genetic algorithm and simulated annealing is discussed as well. You will also see how to enhance training using techniques such as pruning and hybrid training.

Proceedings Of The International Conference On Advanced Intelligent Systems And Informatics 2016

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Author : Aboul Ella Hassanien
language : en
Publisher: Springer
Release Date : 2016-10-20

Proceedings Of The International Conference On Advanced Intelligent Systems And Informatics 2016 written by Aboul Ella Hassanien and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-10-20 with Technology & Engineering categories.

This book gathers the proceedings of the 2nd International Conference on Advanced Intelligent Systems and Informatics (AISI2016), which took place in Cairo, Egypt during October 24–26, 2016. This international interdisciplinary conference, which highlighted essential research and developments in the field of informatics and intelligent systems, was organized by the Scientific Research Group in Egypt (SRGE) and sponsored by the IEEE Computational Intelligence Society (Egypt chapter) and the IEEE Robotics and Automation Society (Egypt Chapter). The book’s content is divided into four main sections: Intelligent Language Processing, Intelligent Systems, Intelligent Robotics Systems, and Informatics.