Machine Learning In Java


Machine Learning In Java
Author: AshishSingh Bhatia
Publisher: Packt Publishing Ltd
ISBN: 1788473892
Size: 13.53 MB
Format: PDF, ePub
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Machine Learning In Java

Machine Learning In Java by AshishSingh Bhatia, Machine Learning In Java Books available in PDF, EPUB, Mobi Format. Download Machine Learning In Java books, 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.


Machine Learning in Java
Language: en
Pages: 300
Authors: AshishSingh Bhatia, Bostjan Kaluza
Categories: Computers
Type: BOOK - Published: 2018-11-28 - Publisher: Packt Publishing Ltd
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
Machine Learning in Java
Language: en
Pages: 258
Authors: Bostjan Kaluza
Categories: Computers
Type: BOOK - Published: 2016-04-29 - Publisher: Packt Publishing Ltd
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
Mastering Java Machine Learning
Language: en
Pages: 556
Authors: Dr. Uday Kamath, Krishna Choppella
Categories: Computers
Type: BOOK - Published: 2017-07-11 - Publisher: Packt Publishing Ltd
Become an advanced practitioner with this progressive set of master classes on application-oriented machine learning About This Book Comprehensive coverage of key topics in machine learning with an emphasis on both the theoretical and practical aspects More than 15 open source Java tools in a wide range of techniques, with
Java Deep Learning Cookbook
Language: en
Pages: 304
Authors: Rahul Raj
Categories: Computers
Type: BOOK - Published: 2019-11-08 - Publisher: Packt Publishing Ltd
Use Java and Deeplearning4j to build robust, scalable, and highly accurate AI models from scratch Key Features Install and configure Deeplearning4j to implement deep learning models from scratch Explore recipes for developing, training, and fine-tuning your neural network models in Java Model neural networks using datasets containing images, text, and
Machine learning in practice – from PyTorch model to Kubeflow in the cloud for BigData
Language: ru
Pages:
Authors: Eugeny Shtoltc
Categories: Computers
Type: BOOK - Published: 2020-12-26 - Publisher: Litres
In this book, the Chief Architect of the Department of Architecture and Management of Technical Architecture (Cloud Native Competence Center and the Corporate University of Architects) of Sberbank shares his knowledge and experience with readers in the field of ML. received in the work of the School of Architects and.
Machine Learning: End-to-End guide for Java developers
Language: en
Pages: 1159
Authors: Richard M. Reese, Jennifer L. Reese, Bostjan Kaluza, Dr. Uday Kamath, Krishna Choppella
Categories: Computers
Type: BOOK - Published: 2017-10-05 - Publisher: Packt Publishing Ltd
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
Practical Java Machine Learning
Language: en
Pages: 392
Authors: Mark Wickham
Categories: Computers
Type: BOOK - Published: 2018-10-23 - Publisher: Apress
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
Hands-On Java Deep Learning for Computer Vision
Language: en
Pages: 260
Authors: Klevis Ramo
Categories: Computers
Type: BOOK - Published: 2019-02-21 - Publisher: Packt Publishing Ltd
Leverage the power of Java and deep learning to build production-grade Computer Vision applications Key Features Build real-world Computer Vision applications using the power of neural networks Implement image classification, object detection, and face recognition Know best practices on effectively building and deploying deep learning models in Java Book Description
Machine Learning
Language: en
Pages: 408
Authors: Jason Bell
Categories: Mathematics
Type: BOOK - Published: 2014-10-20 - Publisher: John Wiley & Sons
Dig deep into the data with a hands-on guide to machinelearning Machine Learning: Hands-On for Developers and TechnicalProfessionals provides hands-on instruction and fully-codedworking examples for the most common machine learning techniquesused by developers and technical professionals. The book contains abreakdown of each ML variant, explaining how it works and how
Data Mining
Language: en
Pages: 371
Authors: Ian H. Witten, Witten, Ian H. Witten, Eibe Frank
Categories: Computers
Type: BOOK - Published: 2000 - Publisher: Morgan Kaufmann
This book offers a thorough grounding in machine learning concepts combined with practical advice on applying machine learning tools and techniques in real-world data mining situations. Clearly written and effectively illustrated, this book is ideal for anyone involved at any level in the work of extracting usable knowledge from large