Java Artificial Intelligence

Java Artificial Intelligence

This book is well written and every lesson is very clearly described. " - Patrick Garrity, from Amazon.com " When I saw this book, I was immediately drawn to the title of the book. I am glad that I got the chance to download this book.

Author: Code Well Academy

Publisher: Createspace Independent Publishing Platform

ISBN: 1530826888

Category:

Page: 166

View: 479

Design the MIND of a Robotic Thinker! " The author of this book did an excellent job and by reading this book I am impressed. This book is well written and every lesson is very clearly described. " " - Patrick Garrity, from Amazon.com " " When I saw this book, I was immediately drawn to the title of the book. I am glad that I got the chance to download this book. " " - Jasmine Torres, from Amazon.com " " Code Well Academy put together a very comprehensive easy to read guide to walk me through from start to finish. " " - Jessica Cece, from Amazon.com " * * INCLUDED BONUS: a Quick-start guide to Learning Java in less than a Day! * * How would you like to Create the Next SIRI? Artificial Intelligence. One of the most brilliant creations of mankind. No longer a sci-fi fantasy, but a realistic approach to making work more efficient and lives easier. And the best news? It's not that complicated after all Does it require THAT much advanced math? NO! And are you paying THOUSANDS of dollars just to learn this information? NO! Hundreds? Not even close. Within this book's pages, you'll find GREAT coding skills to learn - and more. Just some of the questions and topics include: - Complicated scheduling problem? Here's how to solve it. - How good are your AI algorithms? Analysis for Efficiency - How to interpret a system into logical code for the AI - How would an AI system would diagnose a system? We show you... - Getting an AI agent to solve problems for you and Much, much more! World-Class Training This book breaks your training down into easy-to-understand modules. It starts from the very essentials of algorithms and program procedures, so you can write great code - even as a beginner!
Categories:

Machine Learning in Java

Machine Learning in Java

You should be familiar with Java programming and some basic data mining concepts to make the most of this book, but no prior experience with machine learning is required.

Author: AshishSingh Bhatia

Publisher: Packt Publishing Ltd

ISBN: 9781788473897

Category: Computers

Page: 300

View: 508

Leverage the power of Java and its associated machine learning libraries to build powerful predictive models Key Features Solve predictive modeling problems using the most popular machine learning Java libraries Explore data processing, machine learning, and NLP concepts using JavaML, WEKA, MALLET libraries Practical examples, tips, and tricks to help you understand applied machine learning in Java Book Description As the amount of data in the world continues to grow at an almost incomprehensible rate, being able to understand and process data is becoming a key differentiator for competitive organizations. Machine learning applications are everywhere, from self-driving cars, spam detection, document search, and trading strategies, to speech recognition. This makes machine learning well-suited to the present-day era of big data and Data Science. The main challenge is how to transform data into actionable knowledge. Machine Learning in Java will provide you with the techniques and tools you need. You will start by learning how to apply machine learning methods to a variety of common tasks including classification, prediction, forecasting, market basket analysis, and clustering. The code in this book works for JDK 8 and above, the code is tested on JDK 11. Moving on, you will discover how to detect anomalies and fraud, and ways to perform activity recognition, image recognition, and text analysis. By the end of the book, you will have explored related web resources and technologies that will help you take your learning to the next level. By applying the most effective machine learning methods to real-world problems, you will gain hands-on experience that will transform the way you think about data. What you will learn Discover key Java machine learning libraries Implement concepts such as classification, regression, and clustering Develop a customer retention strategy by predicting likely churn candidates Build a scalable recommendation engine with Apache Mahout Apply machine learning to fraud, anomaly, and outlier detection Experiment with deep learning concepts and algorithms Write your own activity recognition model for eHealth applications Who this book is for If you want to learn how to use Java's machine learning libraries to gain insight from your data, this book is for you. 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 with ease. You should be familiar with Java programming and some basic data mining concepts to make the most of this book, but no prior experience with machine learning is required.
Categories: Computers

Hands On Artificial Intelligence with Java for Beginners

Hands On Artificial Intelligence with Java for Beginners

What you will learn Leverage different Java packages and tools such as Weka, RapidMiner, and Deeplearning4j, among others Build machine learning models using supervised and unsupervised machine learning techniques Implement different deep ...

Author: Nisheeth Joshi

Publisher: Packt Publishing Ltd

ISBN: 9781789531022

Category: Computers

Page: 144

View: 304

Build, train, and deploy intelligent applications using Java libraries Key Features Leverage the power of Java libraries to build smart applications Build and train deep learning models for implementing artificial intelligence Learn various algorithms to automate complex tasks Book Description Artificial intelligence (AI) is increasingly in demand as well as relevant in the modern world, where everything is driven by technology and data. AI can be used for automating systems or processes to carry out complex tasks and functions in order to achieve optimal performance and productivity. Hands-On Artificial Intelligence with Java for Beginners begins by introducing you to AI concepts and algorithms. You will learn about various Java-based libraries and frameworks that can be used in implementing AI to build smart applications. In addition to this, the book teaches you how to implement easy to complex AI tasks, such as genetic programming, heuristic searches, reinforcement learning, neural networks, and segmentation, all with a practical approach. By the end of this book, you will not only have a solid grasp of AI concepts, but you'll also be able to build your own smart applications for multiple domains. What you will learn Leverage different Java packages and tools such as Weka, RapidMiner, and Deeplearning4j, among others Build machine learning models using supervised and unsupervised machine learning techniques Implement different deep learning algorithms in Deeplearning4j and build applications based on them Study the basics of heuristic searching and genetic programming Differentiate between syntactic and semantic similarity among texts Perform sentiment analysis for effective decision making with LingPipe Who this book is for Hands-On Artificial Intelligence with Java for Beginners is for Java developers who want to learn the fundamentals of artificial intelligence and extend their programming knowledge to build smarter applications.
Categories: Computers

Kalaha in Java An Experiment in Artificial Intelligence and Networking

Kalaha in Java  An Experiment in Artificial Intelligence and Networking

This report is based on an experiment in developing a Kalaha game application in Java where it explores the areas of Artificial Intelligence in two-player games with perfect information, and networking.

Author:

Publisher:

ISBN: OCLC:690623199

Category:

Page:

View: 377

This report is based on an experiment in developing a Kalaha game application in Java where it explores the areas of Artificial Intelligence in two-player games with perfect information, and networking. In AI aspect, the computer player of the program whom a user can choose to play against finds intelligent moves by using minimax algorithm with alpha-beta pruning. In networking aspect, the game is able to play against another human player via a network. Hence, theoretical parts that are applied in implementing the program such as game trees, minimax algorithm, alpha-beta pruning and client-server model are discussed. The design of the program is based on object-oriented programming and there are classes that can be extended for implementing any two-player game. As the conclusion, over all result of the implementation is satisfactory, since the program meets the requirements that have been set.
Categories:

Machine Learning in Java

Machine Learning in Java

Design, build, and deploy your own machine learning 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 ...

Author: Bostjan Kaluza

Publisher: Packt Publishing Ltd

ISBN: 9781784390365

Category: Computers

Page: 258

View: 497

Design, build, and deploy your own machine learning 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 Packed with practical advice and tips to help you get to grips with applied machine learning Who This Book Is For If you want to learn how to use Java's machine learning libraries to gain insight from your data, this book is for you. 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. You should be familiar with Java programming and data mining concepts to make the most of this book, but no prior experience with data mining packages is necessary. What You Will Learn Understand the basic steps of applied machine learning and how to differentiate among various machine learning approaches Discover key Java machine learning libraries, what each library brings to the table, and what kind of problems each are able to solve Learn how to implement classification, regression, and clustering Develop a sustainable strategy for customer retention by predicting likely churn candidates Build a scalable recommendation engine with Apache Mahout Apply machine learning to fraud, anomaly, and outlier detection Experiment with deep learning concepts, algorithms, and the toolbox for deep learning Write your own activity recognition model for eHealth applications using mobile sensors In Detail As the amount of data continues to grow at an almost incomprehensible rate, being able to understand and process data is becoming a key differentiator for competitive organizations. Machine learning applications are everywhere, from self-driving cars, spam detection, document search, and trading strategies, to speech recognition. This makes machine learning well-suited to the present-day era of Big Data and Data Science. The main challenge is how to transform data into actionable knowledge. Machine Learning in Java will provide you with the techniques and tools you need to quickly gain insight from complex data. You will start by learning how to apply machine learning methods to a variety of common tasks including classification, prediction, forecasting, market basket analysis, and clustering. Moving on, you will discover how to detect anomalies and fraud, and ways to perform activity recognition, image recognition, and text analysis. By the end of the book, you will explore related web resources and technologies that will help you take your learning to the next level. By applying the most effective machine learning methods to real-world problems, you will gain hands-on experience that will transform the way you think about data. Style and approach This is a practical tutorial that uses hands-on examples to step through some real-world applications of machine learning. Without shying away from the technical details, you will explore machine learning with Java libraries using clear and practical examples. You will explore how to prepare data for analysis, choose a machine learning method, and measure the success of the process.
Categories: Computers

Mancala in Java

Mancala in Java

Author: Adam Cofer

Publisher:

ISBN: OCLC:650091800

Category: Mancala (Game)

Page: 52

View: 521

Categories: Mancala (Game)

Hands on AI with Java

Hands on AI with Java

This book shows you how to: * Give computer game characters role-playing and decision-making skills * Simulate evolution to find solutions to hard problems * Develop machine-to-human text interactions for help desks, adventure games, ...

Author: Edwin Wise

Publisher: McGraw-Hill Professional

ISBN: 0071424962

Category: Computers

Page: 340

View: 923

First the author introduces the techniques of AI, then uses Java to fully illustrate them. The Java code cited in this text can be used in a number of situations such as games, robotics, Web agents and more.
Categories: Computers

Introduction to Neural Networks with Java

Introduction to Neural Networks with Java

Introduction to Neural Networks in Java, Second Edition, introduces the Java programmer to the world of Neural Networks and Artificial Intelligence.

Author: Jeff Heaton

Publisher: Heaton Research, Inc.

ISBN: 9781604390087

Category: Computers

Page: 440

View: 298

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.
Categories: Computers

Practical Java Machine Learning

Practical Java Machine Learning

Build machine learning (ML) solutions for Java development. This book shows you that when designing ML apps, data is the key driver and must be considered throughout all phases of the project life cycle.

Author: Mark Wickham

Publisher: Apress

ISBN: 9781484239513

Category: Computers

Page: 392

View: 675

Build machine learning (ML) solutions for Java development. This book shows you that when designing ML apps, data is the key driver and must be considered throughout all phases of the project life cycle. Practical Java Machine Learning helps you understand the importance of data and how to organize it for use within your ML project. You will be introduced to tools which can help you identify and manage your data including JSON, visualization, NoSQL databases, and cloud platforms including Google Cloud Platform and Amazon Web Services. Practical Java Machine Learning includes multiple projects, with particular focus on the Android mobile platform and features such as sensors, camera, and connectivity, each of which produce data that can power unique machine learning solutions. You will learn to build a variety of applications that demonstrate the capabilities of the Google Cloud Platform machine learning API, including data visualization for Java; document classification using the Weka ML environment; audio file classification for Android using ML with spectrogram voice data; and machine learning using device sensor data. After reading this book, you will come away with case study examples and projects that you can take away as templates for re-use and exploration for your own machine learning programming projects with Java. What You Will Learn Identify, organize, and architect the data required for ML projects Deploy ML solutions in conjunction with cloud providers such as Google and Amazon Determine which algorithm is the most appropriate for a specific ML problem Implement Java ML solutions on Android mobile devices Create Java ML solutions to work with sensor data Build Java streaming based solutions Who This Book Is For Experienced Java developers who have not implemented machine learning techniques before.
Categories: Computers

Practical Java Programming for IoT AI and Blockchain

Practical Java Programming for IoT  AI  and Blockchain

—Albert Einstein 8.1 What Is Artificial Intelligence? 8.2 Neural Networks 8.3
Machine Learning 8.4 Deep Learning 8.5 Java AI Libraries 8.6 Java Examples
for Neural Networks 8.7 Java Examples for Machine Learning 8.8 Java Examples
for ...

Author: Perry Xiao

Publisher: John Wiley & Sons

ISBN: 9781119560036

Category: Computers

Page: 480

View: 336

Learn practical uses for some of the hottest tech applications trending among technology professionals We are living in an era of digital revolution. On the horizon, many emerging digital technologies are being developed at a breathtaking speed. Whether we like it or not, whether we are ready or not, digital technologies are going to penetrate more and more, deeper and deeper, into every aspect of our lives. This is going to fundamentally change how we live, how we work, and how we socialize. Java, as a modern high-level programming language, is an excellent tool for helping us to learn these digital technologies, as well as to develop digital applications, such as IoT, AI, Cybersecurity, Blockchain and more. Practical Java Programming uses Java as a tool to help you learn these new digital technologies and to be better prepared for the future changes. Gives you a brief overview for getting started with Java Programming Dives into how you can apply your new knowledge to some of the biggest trending applications today Helps you understand how to program Java to interact with operating systems, networking, and mobile applications Shows you how Java can be used in trending tech applications such as IoT (Internet of Things), AI (Artificial Intelligence), Cybersecurity, and Blockchain Get ready to find out firsthand how Java can be used for connected home devices, healthcare, the cloud, and all the hottest tech applications.
Categories: Computers

Machine Learning End to End guide for Java developers

Machine Learning  End to End guide for Java developers

Develop, Implement and Tuneup your Machine Learning applications using the power of Java programming About This Book Detailed coverage on key machine learning topics with an emphasis on both theoretical and practical aspects Address ...

Author: Richard M. Reese

Publisher: Packt Publishing Ltd

ISBN: 9781788629409

Category: Computers

Page: 1159

View: 777

Develop, Implement and Tuneup your Machine Learning applications using the power of Java programming About This Book Detailed coverage on key machine learning topics with an emphasis on both theoretical and practical aspects Address predictive modeling problems using the most popular machine learning Java libraries A comprehensive course covering a wide spectrum of topics such as machine learning and natural language through practical use-cases Who This Book Is For This course is the right resource for anyone with some knowledge of Java programming who wants to get started with Data Science and Machine learning as quickly as possible. If you want to gain meaningful insights from big data and develop intelligent applications using Java, this course is also a must-have. What You Will Learn Understand key data analysis techniques centered around machine learning Implement Java APIs and various techniques such as classification, clustering, anomaly detection, and more Master key Java machine learning libraries, their functionality, and various kinds of problems that can be addressed using each of them Apply machine learning to real-world data for fraud detection, recommendation engines, text classification, and human activity recognition Experiment with semi-supervised learning and stream-based data mining, building high-performing and real-time predictive models Develop intelligent systems centered around various domains such as security, Internet of Things, social networking, and more In Detail Machine Learning is one of the core area of Artificial Intelligence where computers are trained to self-learn, grow, change, and develop on their own without being explicitly programmed. In this course, we cover how Java is employed to build powerful machine learning models to address the problems being faced in the world of Data Science. The course demonstrates complex data extraction and statistical analysis techniques supported by Java, applying various machine learning methods, exploring machine learning sub-domains, and exploring real-world use cases such as recommendation systems, fraud detection, natural language processing, and more, using Java programming. The course begins with an introduction to data science and basic data science tasks such as data collection, data cleaning, data analysis, and data visualization. The next section has a detailed overview of statistical techniques, covering machine learning, neural networks, and deep learning. The next couple of sections cover applying machine learning methods using Java to a variety of chores including classifying, predicting, forecasting, market basket analysis, clustering stream learning, active learning, semi-supervised learning, probabilistic graph modeling, text mining, and deep learning. The last section highlights real-world test cases such as performing activity recognition, developing image recognition, text classification, and anomaly detection. The course includes premium content from three of our most popular books: Java for Data Science Machine Learning in Java Mastering Java Machine Learning On completion of this course, you will understand various machine learning techniques, different machine learning java algorithms you can use to gain data insights, building data models to analyze larger complex data sets, and incubating applications using Java and machine learning algorithms in the field of artificial intelligence. Style and approach This comprehensive course proceeds from being a tutorial to a practical guide, providing an introduction to machine learning and different machine learning techniques, exploring machine learning with Java libraries, and demonstrating real-world machine learning use cases using the Java platform.
Categories: Computers

Artificial Intelligence in Education

Artificial Intelligence in Education

Modeling. In our experiment we used two existing ontologies – one for Java and
one for C. The Java Ontology was developed for the AES Personal Reader for
eLearning [17]. The ontology is represented in RDFS and can be accessed at ...

Author: Rosemary Luckin

Publisher: IOS Press

ISBN: 9781586037642

Category: Computers

Page: 738

View: 439

" The nature of technology has changed since Artificial Intelligence in Education (AIED) was conceptualised as a research community and Interactive Learning Environments were initially developed. Technology is smaller, more mobile, networked, pervasive and often ubiquitous as well as being provided by the standard desktop PC. This creates the potential for technology supported learning wherever and whenever learners need and want it. However, in order to take advantage of this potential for greater flexibility we need to understand and model learners and the contexts with which they interact in a manner that enables us to design, deploy and evaluate technology to most effectively support learning across multiple locations, subjects and times. The AIED community has much to contribute to this endeavour. This publication contains papers, posters and tutorials from the 2007 Artificial Intelligence in Education conference in Los Angeles, CA, USA. "
Categories: Computers

An Introduction to Artificial Intelligence

An Introduction to Artificial Intelligence

Taken from the various sources which are in public domain. With its application oriented approach and inclusion of recent topics, the book would also be useful to postgraduate students and researchers in this field. —Editor

Author: Manoj Singh

Publisher: Neelkanth Prakashan

ISBN:

Category: Science

Page:

View: 390

Artificial Intelligence is defined as the science of making computers do things that require intelligence when done by humans. Artificial Intelligence has had some success in limited, or simplified, domains. Knowledge Management provides a balance of conceptual and practical aspects of knowledge management offering the opportunity for students and practitioners to understand and effectively consider knowledge management approaches in their organizations. Artificial Intelligence (AI) is the name that has been given to the field of computer science devoted to making machines do things that would require intelligence if done by humans (to paraphrase Minsky). Some are even ambitious enough to say that the goal of AI is to create minds in machines. But it has proven exceedingly difficult to even define words like “intelligence” and “mind”, much less achieve computer implementation. The results of the 40-year history of AI have dampened the spirits of legions of would-be enthusiasts. The most “glamorous” contemporary computer applications are GUI or Java programmes, not AI. Artificial Intelligence has been divided into those concerned with processing of symbolic information and those concerned with Neural Networks. But the Symbolic AI camp has made every effort to exclude Neural Networks from the definition of AI, and the field of “Connectionism” is increasingly regarded as a somewhat independent discipline. The Artificial Intelligence Applications Institute has many project that they are working on to make their computers learn how to operate themselves with less human input. o have more functionality with less input is an operation for AI technology. If it isn’t able or isn’t reliable AUSDA will instruct you on finding alternative software which would better suit your needs. According to AI, the software will try to provide solutions to problems like “identifying the root causes of incidents in which the use of computer software is involved, studying different software development approaches, and identifying aspects of these which are relevant to those root causes producing guidelines for using and improving the development approaches studied, and providing support in the integration of these approaches, so that they can be better used for the development and maintenance of safety critical software.” Machine learning, a branch of artificial intelligence, is a scientific discipline concerned with the design and development of algorithms that allow computers to evolve behaviours based on empirical data, such as from sensor data or databases. A learner can take advantage of examples (data) to capture characteristics of interest of their unknown underlying probability distribution. Data can be seen as examples that illustrate relations between observed variables. A major focus of machine learning research is to automatically learn to recognize complex patterns and make intelligent decisions based on data; the difficulty lies in the fact that the set of all possible behaviours given all possible inputs is too large to be covered by the set of observed examples (training data). Hence the learner must generalize from the given examples, so as to be able to produce a useful output in new cases. Machine learning, like all subjects in artificial intelligence, requires cross-disciplinary proficiency in several areas, such as probability theory, statistics, pattern recognition, cognitive science, data mining, adaptive control, computational neuroscience and theoretical computer science. All the matter is just compiled and edited in nature. Taken from the various sources which are in public domain. With its application oriented approach and inclusion of recent topics, the book would also be useful to postgraduate students and researchers in this field. —Editor
Categories: Science

Intelligent Java Applications for the Internet and Intranets

Intelligent Java Applications for the Internet and Intranets

Focusing on intelligent systems, this book provides the introductory AI material that Java programmers need to create Internet and Intranet applications including online games, search engines, and data-collection tools.

Author: Mark Watson

Publisher: Morgan Kaufmann Pub

ISBN: 1558604200

Category: Computers

Page: 377

View: 447

Internet tools and applications frequently use artificial intelligence (AI) techniques to enable special features and reduced development time. Focusing on intelligent systems, this book provides the introductory AI material that Java programmers need to create Internet and Intranet applications including online games, search engines, and data-collection tools.
Categories: Computers

Classic Computer Science Problems in Java

Classic Computer Science Problems in Java

Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications.

Author: David Kopec

Publisher: Manning Publications

ISBN: 9781617297601

Category: Computers

Page: 225

View: 564

Classic Computer Science Problems in Java will teach you techniques to solve common-but-tricky programming issues. You’ll explore foundational coding methods, fundamental algorithms, and artificial intelligence topics, all through code-centric Java tutorials and computer science exercises. Sharpen your coding skills by exploring established computer science problems! Classic Computer Science Problems in Java challenges you with time-tested scenarios and algorithms. You’ll work through a series of exercises based in computer science fundamentals that are designed to improve your software development abilities, improve your understanding of artificial intelligence, and even prepare you to ace an interview. Classic Computer Science Problems in Java will teach you techniques to solve common-but-tricky programming issues. You’ll explore foundational coding methods, fundamental algorithms, and artificial intelligence topics, all through code-centric Java tutorials and computer science exercises. As you work through examples in search, clustering, graphs, and more, you'll remember important things you've forgotten and discover classic solutions to your "new" problems! Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications.
Categories: Computers

Deep Learning Practical Neural Networks with Java

Deep Learning  Practical Neural Networks with Java

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.

Author: Yusuke Sugomori

Publisher: Packt Publishing Ltd

ISBN: 9781788471718

Category: Computers

Page: 744

View: 654

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
Categories: Computers

Neural Network Programming with Java

Neural Network Programming with Java

Create and unleash the power of neural networks by implementing professional Java code About This Book Learn to build amazing projects using neural networks including forecasting the weather and pattern recognition Explore the Java multi ...

Author: Alan M.F. Souza

Publisher: Packt Publishing Ltd

ISBN: 9781785884948

Category: Computers

Page: 244

View: 185

Create and unleash the power of neural networks by implementing professional Java code About 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 application Who This Book Is For This 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 network In Detail Vast 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 approach This 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.
Categories: Computers

Neural Network Programming with Java

Neural Network Programming with Java

Create and unleash the power of neural networks by implementing professional Java code About This Book Learn to build amazing projects using neural networks including forecasting the weather and pattern recognition Explore the Java multi ...

Author: Fabio M. Soares

Publisher: Packt Publishing Ltd

ISBN: 9781787122970

Category: Computers

Page: 270

View: 231

Create and unleash the power of neural networks by implementing professional Java code About 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 application Who This Book Is For This 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 strategies In Detail Want 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. Style and approach This book takes you on a steady learning curve, teaching you the important concepts while being rich in examples. You'll be able to relate to the examples in the book while implementing neural networks in your day-to-day applications.
Categories: Computers

Logics in Artificial Intelligence

Logics in Artificial Intelligence

Ca Calejo , M . : Inter Prolog , a declarative Java - Prolog interface , in Procs .
Logic Programming for Artificial Intelligence and Information Systems ( thematic
Workshop of the 10th Portuguese Conference on Artificial Intelligence ) , Porto ...

Author:

Publisher:

ISBN: UOM:39015058885438

Category: Artificial intelligence

Page:

View: 183

Categories: Artificial intelligence