Неизв. - Java Data Science Cookbook
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Copyright 2017 Packt Publishing
All rights reserved. No part of this book may be reproduced, stored in a retrieval system, or transmitted in any form or by any means, without the prior written permission of the publisher, except in the case of brief quotations embedded in critical articles or reviews.
Every effort has been made in the preparation of this book to ensure the accuracy of the information presented. However, the information contained in this book is sold without warranty, either express or implied. Neither the author, nor Packt Publishing, and its dealers and distributors will be held liable for any damages caused or alleged to be caused directly or indirectly by this book.
Packt Publishing has endeavored to provide trademark information about all of the companies and products mentioned in this book by the appropriate use of capitals. However, Packt Publishing cannot guarantee the accuracy of this information.
First published: March 2017
Production reference: 1240317
Published by Packt Publishing Ltd.
Livery Place
35 Livery Street
Birmingham
B3 2PB, UK.
ISBN 978-1-78712-253-6
www.packtpub.com
Author Rushdi Shams | Copy Editors Vikrant Phadke Manisha Sinha |
Reviewer Prashant Verma | Project Coordinator Nidhi Joshi |
Commissioning Editor Veena Pagare | Proofreader Safis Editing |
Acquisition Editor Ajith Menon | Indexer Aishwarya Gangawane |
Content Development Editor Cheryl Dsa | Graphics Tania Dutta |
Technical Editor Dharmendra Yadav | Production Coordinator Arvindkumar Gupta |
Rushdi Shams has a PhD on application of machine learning in Natural Language Processing (NLP) problem areas from Western University, Canada. Before starting work as a machine learning and NLP specialist in industry, he was engaged in teaching undergrad and grad courses. He has been successfully maintaining his YouTube channel named "Learn with Rushdi" for learning computer technologies.
I would like to acknowledge the Almighty Allah for giving me the strength, support, and knowledge to finish the book.
I extend my thanks to my family members, friends, and colleagues for continuous support, encouragement, and constructive criticism.
I would also like to thank Ajith and Cheryl from Packt for their continuous and spontaneous collaboration with me.
Prashant Verma started his IT career in 2011 as a Java developer at Ericsson, working in the telecom domain. After a couple of years of Java EE experience, he moved into the big data domain, and has worked on almost all the popular big data technologies such as Hadoop, Spark, Kafka, Flume, Mongo, Cassandra, and so on. He has also worked in Scala and Python. Currently, he works with QA Infotech as Lead Data Engineer, working on solving e-learning domain problems using data analytics and machine learning.
Prashant has also worked on Apache Spark for Java Developers , Packt as a Technical Reviewer.
I want to thank Packt Publishing for giving me the chance to review the book, as well as my employer and my family for their patience while I was busy working on this book.
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To my lovely wife, Mah-Zereen, and adorable daughter, Ruayda.
Data science is a popular field for specialization nowadays and covers the broad spectrum of artificial intelligence, such as data processing, information retrieval, machine learning, natural language processing, big data, deep neural networks, and data visualization. In this book, we will understand the techniques that are both modern and smart and presented as easy-to-follow recipes for over 70 problems.
Keeping in mind the high demand for quality data scientists, we have compiled recipes using core Java as well as well-known, classic, and state-of-the-art data science libraries written in Java. We start with the data collection and cleaning process. Then we see how the obtained data can be indexed and searched. Afterwards, we cover statistics both descriptive and inferential and their application to data. Then, we have two back-to-back chapters on the application of machine learning on data that can be foundation for building any smart system. Modern information retrieval and natural language processing techniques are also covered. Big data is an emerging field, and a few aspects of this popular field are also covered. We also cover the very basics of deep learning using deep neural networks. Finally, we learn how to represent data and information obtained from data using meaningful visuals or graphs.
The book is aimed at anyone who has an interest in data science and plans to apply data science using Java to understand underlying data better.
, Obtaining and Cleaning Data , covers different ways to read and write data as well as to clean it to get rid of noise. It also familiarizes the readers with different data file types, such as PDF, ASCII, CSV, TSV, XML, and JSON. The chapter also covers recipes for extracting web data.
, Indexing and Searching Data , covers how to index data for fast searching using Apache Lucene. The techniques described in this chapter can be seen as the basis for modern-day search techniques.
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