Big Data
Management of massive volume of both structured and unstructured data that is so large it is difficult to process using traditional database and software techniques.
All categoriesBooks under this sub-category (18 books)
![[Sign-up required] Practical Data Analysis - Transform, model, and visualize your data through hands-on projects, developed in open source tools](https://www.freetechbooks.com/uploads/1493802708-9781783280995-PRACTICAL_DATA_ANALYSIS_rs.jpg)
Post date: 03 May 2017
A hands-on guide to understanding the nature of your data and turn it into insight. Presents a detailed exploration of the current work in data analysis through self-contained projects.
A hands-on guide to understanding the nature of your data and turn it into insight. Presents a detailed exploration of the current work in data analysis through self-contained projects.
Post date: 03 May 2017A hands-on guide to understanding the nature of your data and turn it into insight. Presents a detailed exploration of the current work in data analysis through self-contained projects.
An Introduction to Data Science
Post date: 28 Jun 2016This book provides non-technical readers with a gentle introduction to essential concepts and activities of data science.
Publication date: 31 Dec 2012
License: Creative Commons Attribution-NonCommercial-ShareAlike 3.0 Unported
Document Type: Book
License: Creative Commons Attribution-NonCommercial-ShareAlike 3.0 Unported
Document Type: Book
An Introduction to Data Science
Post date: 28 Jun 2016This book provides non-technical readers with a gentle introduction to essential concepts and activities of data science.
Publication date: 31 Dec 2012
License: Creative Commons Attribution-NonCommercial-ShareAlike 3.0 Unported Document Type: Book
License: Creative Commons Attribution-NonCommercial-ShareAlike 3.0 Unported Document Type: Book
Post date: 29 Jun 2016
Lecture notes for Applied Data Science course at Columbia University. It focuses more on the statistics edge, while also teaching readers some basic programming skill.
Lecture notes for Applied Data Science course at Columbia University. It focuses more on the statistics edge, while also teaching readers some basic programming skill.
Publication date: 31 Dec 2012
Post date: 29 Jun 2016Lecture notes for Applied Data Science course at Columbia University. It focuses more on the statistics edge, while also teaching readers some basic programming skill.
Publication date: 31 Dec 2012
Post date: 03 Oct 2016
Recaps the trends, tools, applications, and forecasts of big data. Includes data-driven cultures, data science, data pipelines, big data architecture and infrastructure, the Internet of Things and real time, applications of big data, security, and ethics.
Recaps the trends, tools, applications, and forecasts of big data. Includes data-driven cultures, data science, data pipelines, big data architecture and infrastructure, the Internet of Things and real time, applications of big data, security, and ethics.
Post date: 03 Oct 2016Recaps the trends, tools, applications, and forecasts of big data. Includes data-driven cultures, data science, data pipelines, big data architecture and infrastructure, the Internet of Things and real time, applications of big data, security, and ethics.
Big Data on Real-World Applications
Post date: 10 Nov 2016Describes the importance of the Big Data era and how existing information systems are required to be adapted to face up the problems derived from the management of massive datasets.
Publisher:
InTech
Publication date: 20 Jul 2016
License: Creative Commons Attribution 3.0 Unported
Document Type: Book
Publication date: 20 Jul 2016
License: Creative Commons Attribution 3.0 Unported
Document Type: Book
Big Data on Real-World Applications
Post date: 10 Nov 2016Describes the importance of the Big Data era and how existing information systems are required to be adapted to face up the problems derived from the management of massive datasets.
Publisher:
InTech
Publication date: 20 Jul 2016
License: Creative Commons Attribution 3.0 Unported Document Type: Book
Publication date: 20 Jul 2016
License: Creative Commons Attribution 3.0 Unported Document Type: Book
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Post date: 10 Apr 2016
In this in-depth report, data scientist DJ Patil explains the skills,perspectives, tools and processes that position data science teams for success.
In this in-depth report, data scientist DJ Patil explains the skills,perspectives, tools and processes that position data science teams for success.
Post date: 10 Apr 2016In this in-depth report, data scientist DJ Patil explains the skills,perspectives, tools and processes that position data science teams for success.
Data-Intensive Text Processing with MapReduce
Post date: 13 Apr 2016This book focuses on MapReduce algorithm design, with an emphasis on text processing algorithms common in natural language processing, information retrieval, and machine learning.
Data-Intensive Text Processing with MapReduce
Post date: 13 Apr 2016This book focuses on MapReduce algorithm design, with an emphasis on text processing algorithms common in natural language processing, information retrieval, and machine learning.
Disruptive Possibilities: How Big Data Changes Everything
Post date: 03 Oct 2016Provides an historically-informed overview of big data through a wide range of topics, from the evolution of commodity supercomputing and the simplicity of big data technology, to the ways conventional clouds differ from Hadoop analytics clouds.
Disruptive Possibilities: How Big Data Changes Everything
Post date: 03 Oct 2016Provides an historically-informed overview of big data through a wide range of topics, from the evolution of commodity supercomputing and the simplicity of big data technology, to the ways conventional clouds differ from Hadoop analytics clouds.
Post date: 29 Sep 2016
Provides the background needed for a modern theoretical course in computer science.
Provides the background needed for a modern theoretical course in computer science.
Publication date: 11 Apr 2014
Document Type: Textbook
Document Type: Textbook
Post date: 29 Sep 2016Provides the background needed for a modern theoretical course in computer science.
Publication date: 11 Apr 2014
Document Type: Textbook
Document Type: Textbook
Hadoop and Kerberos: The Madness Beyond the Gate
Post date: 11 Apr 2016An introduction to Hadoop and Kerberos.
Hadoop and Kerberos: The Madness Beyond the Gate
Post date: 11 Apr 2016An introduction to Hadoop and Kerberos.
Post date: 02 Jun 2016
An introduction to Big Data and Apache Hadoop. This book aims to make Hadoop knowledge accessible to a wider audience, not just to the highly technical.
An introduction to Big Data and Apache Hadoop. This book aims to make Hadoop knowledge accessible to a wider audience, not just to the highly technical.
Publication date: 01 Jan 2014
License: Creative Commons Attribution-NonCommercial-ShareAlike 3.0 Unported
License: Creative Commons Attribution-NonCommercial-ShareAlike 3.0 Unported
Post date: 02 Jun 2016An introduction to Big Data and Apache Hadoop. This book aims to make Hadoop knowledge accessible to a wider audience, not just to the highly technical.
Publication date: 01 Jan 2014
License: Creative Commons Attribution-NonCommercial-ShareAlike 3.0 Unported
License: Creative Commons Attribution-NonCommercial-ShareAlike 3.0 Unported
Post date: 21 Mar 2018
With this concise book, you'll learn how to use Python with the Hadoop Distributed File System (HDFS), MapReduce, the Apache Pig platform and Pig Latin script, and the Apache Spark cluster-computing framework.
With this concise book, you'll learn how to use Python with the Hadoop Distributed File System (HDFS), MapReduce, the Apache Pig platform and Pig Latin script, and the Apache Spark cluster-computing framework.
Post date: 21 Mar 2018With this concise book, you'll learn how to use Python with the Hadoop Distributed File System (HDFS), MapReduce, the Apache Pig platform and Pig Latin script, and the Apache Spark cluster-computing framework.
Linked Open Data - Creating Knowledge Out of Interlinked Data: Results of the LOD2 Project
Post date: 26 Oct 2016Presents an overview of the results of the 4-year research project 'LOD2 – Creating Knowledge out of Interlinked Data', the goal of which was realizing the Semantic Web vision of making the Web a global, distributed, semantics-based information system.
Publisher:
Springer-Verlag GmbH
Publication date: 31 Dec 2014
License: Creative Commons Attribution-NonCommercial 4.0 International
Document Type: Book
Publication date: 31 Dec 2014
License: Creative Commons Attribution-NonCommercial 4.0 International
Document Type: Book
Linked Open Data - Creating Knowledge Out of Interlinked Data: Results of the LOD2 Project
Post date: 26 Oct 2016Presents an overview of the results of the 4-year research project 'LOD2 – Creating Knowledge out of Interlinked Data', the goal of which was realizing the Semantic Web vision of making the Web a global, distributed, semantics-based information system.
Publisher:
Springer-Verlag GmbH
Publication date: 31 Dec 2014
License: Creative Commons Attribution-NonCommercial 4.0 International Document Type: Book
Publication date: 31 Dec 2014
License: Creative Commons Attribution-NonCommercial 4.0 International Document Type: Book
Planning for Big Data: A CIO's Handbook to the Changing Data Landscape
Post date: 11 Apr 2016The aim of this book is to help you understand what big data is, why it matters, and where to get started. If you’re already working with big data, hand this book to your colleagues or executives to help them better appreciate the issues and possibilities
Planning for Big Data: A CIO's Handbook to the Changing Data Landscape
Post date: 11 Apr 2016The aim of this book is to help you understand what big data is, why it matters, and where to get started. If you’re already working with big data, hand this book to your colleagues or executives to help them better appreciate the issues and possibilities
R Programming for Data Science
Post date: 04 Aug 2016Covers the fundamentals of R programming, using the same material developed as part of the industry-leading Johns Hopkins Data Science Specialization.
R Programming for Data Science
Post date: 04 Aug 2016Covers the fundamentals of R programming, using the same material developed as part of the industry-leading Johns Hopkins Data Science Specialization.
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