Data Science

An interdisciplinary field about processes and systems to extract knowledge or insights from data in various forms, either structured or unstructured.

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Books under this sub-category (17 books)

An Introduction to Data Science

Post date: 28 Jun 2016
This book provides non-technical readers with a gentle introduction to essential concepts and activities of data science.
 
An Introduction to Data Science

An Introduction to Data Science

Post date: 28 Jun 2016
This book provides non-technical readers with a gentle introduction to essential concepts and activities of data science.



Applied Data Science

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.
 
Applied Data Science

Applied Data Science

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.

Big Data Now: 2015 Edition

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.
Author(s): O'Reilly Media Inc.
Publication date: 31 Jan 2016
Document Type: Book
Tags: Big Data Data Science
 
Big Data Now: 2015 Edition

Big Data Now: 2015 Edition

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.
Author(s): O'Reilly Media Inc.
Publication date: 31 Jan 2016
Document Type: Book
Tags: Big Data Data Science


Building Data Science Teams

Post date: 09 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.
Author(s): DJ Patil
Publication date: 01 Sep 2011
Tags: Big Data Data Science
 
Building Data Science Teams

Building Data Science Teams

Post date: 09 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.
Author(s): DJ Patil
Publication date: 01 Sep 2011
Tags: Big Data Data Science


D3 Tips and Tricks v3.x: Interactive Data Visualization in a Web Browser

Post date: 11 Dec 2016
Over 600 pages of tips and tricks for using d3.js, one of the leading data visualization tools for the web. It's aimed at getting you started and moving you forward. Includes over 50 downloadable code examples.
Author(s): Malcolm Maclean
Publication date: 15 Aug 2016
Document Type: Book
Tags: Data Science JavaScript Web Design and Development
 
D3 Tips and Tricks v3.x: Interactive Data Visualization in a Web Browser

D3 Tips and Tricks v3.x: Interactive Data Visualization in a Web Browser

Post date: 11 Dec 2016
Over 600 pages of tips and tricks for using d3.js, one of the leading data visualization tools for the web. It's aimed at getting you started and moving you forward. Includes over 50 downloadable code examples.
Author(s): Malcolm Maclean
Publication date: 15 Aug 2016
Document Type: Book
Tags: Data Science JavaScript Web Design and Development


Data Science with Microsoft SQL Server 2016

Post date: 25 Oct 2016
This book covers the combined environments of RDBMS and the R language inside Microsoft SQL Server 2016. Readers can learn to use this new capability, and practical, hands-on examples of using SQL Server R Services to create real-world solutions.
 
Data Science with Microsoft SQL Server 2016

Data Science with Microsoft SQL Server 2016

Post date: 25 Oct 2016
This book covers the combined environments of RDBMS and the R language inside Microsoft SQL Server 2016. Readers can learn to use this new capability, and practical, hands-on examples of using SQL Server R Services to create real-world solutions.

Disruptive Possibilities: How Big Data Changes Everything

Post date: 03 Oct 2016
Provides 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.
Author(s): Jeff Needham
Publication date: 08 Jul 2013
Document Type: Book
Tags: Big Data Data Science
 
Disruptive Possibilities: How Big Data Changes Everything

Disruptive Possibilities: How Big Data Changes Everything

Post date: 03 Oct 2016
Provides 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.
Author(s): Jeff Needham
Publication date: 08 Jul 2013
Document Type: Book
Tags: Big Data Data Science


Exploratory Data Analysis with R

Post date: 13 Dec 2016
This book teaches you to use R to effectively visualize and explore complex datasets.
Author(s): Roger D. Peng
Publication date: 20 Jul 2016
Document Type: Book
Tags: Data Science R
 
Exploratory Data Analysis with R

Exploratory Data Analysis with R

Post date: 13 Dec 2016
This book teaches you to use R to effectively visualize and explore complex datasets.
Author(s): Roger D. Peng
Publication date: 20 Jul 2016
Document Type: Book
Tags: Data Science R


Exploring Data Science

Post date: 10 Nov 2016
Introduces readers to various areas in data science and explains which methodologies work best for each, with practical examples in R, Python, and other languages.
Author(s): John Mount Nina Zumel
Publication date: 01 Jun 2016
License: Standard Copyright License
Document Type: Book
Tags: Data Science
 
Exploring Data Science

Exploring Data Science

Post date: 10 Nov 2016
Introduces readers to various areas in data science and explains which methodologies work best for each, with practical examples in R, Python, and other languages.
Author(s): John Mount Nina Zumel
Publication date: 01 Jun 2016
License: Standard Copyright License
Document Type: Book
Tags: Data Science


Foundations of Data Science

Post date: 29 Sep 2016
Provides the background needed for a modern theoretical course in computer science.
Author(s): John Hopcroft Ravindran Kannan
Publication date: 11 Apr 2014
Document Type: Textbook
Tags: Big Data Data Science Introduction to Computer Science Machine Learning
 
Foundations of Data Science

Foundations of Data Science

Post date: 29 Sep 2016
Provides the background needed for a modern theoretical course in computer science.
Author(s): John Hopcroft Ravindran Kannan
Publication date: 11 Apr 2014
Document Type: Textbook
Tags: Big Data Data Science Introduction to Computer Science Machine Learning


Python for Everybody: Exploring Data In Python 3

Post date: 07 Sep 2016
This book provides an Informatics-oriented introduction to programming. It focuses on using Python to solve data analysis problems common in the world of Informatics.
 
Python for Everybody: Exploring Data In Python 3

Python for Everybody: Exploring Data In Python 3

Post date: 07 Sep 2016
This book provides an Informatics-oriented introduction to programming. It focuses on using Python to solve data analysis problems common in the world of Informatics.

Python for Informatics: Exploring Information

Post date: 13 Jan 2011
A remix of Allen B. Downey's Think Python, the overall book structure has been changed to get to doing data analysis problems as quickly as possible and have a series of running examples and exercises about data analysis from the very beginning.
 
Python for Informatics: Exploring Information

Python for Informatics: Exploring Information

Post date: 13 Jan 2011
A remix of Allen B. Downey's Think Python, the overall book structure has been changed to get to doing data analysis problems as quickly as possible and have a series of running examples and exercises about data analysis from the very beginning.

R for Data Science: Visualize, Model, Transform, Tidy, and Import Data

Post date: 16 Dec 2016
This book will teach you how to do data science with R: You'll learn how to get your data into R, get it into the most useful structure, transform it, visualize it and model it.
 
R for Data Science: Visualize, Model, Transform, Tidy, and Import Data

R for Data Science: Visualize, Model, Transform, Tidy, and Import Data

Post date: 16 Dec 2016
This book will teach you how to do data science with R: You'll learn how to get your data into R, get it into the most useful structure, transform it, visualize it and model it.

R Programming for Data Science

Post date: 04 Aug 2016
Covers the fundamentals of R programming, using the same material developed as part of the industry-leading Johns Hopkins Data Science Specialization.
Author(s): Roger D. Peng
Publication date: 03 Aug 2016
Document Type: Book
Tags: Big Data Data Science R Statistics
 
R Programming for Data Science

R Programming for Data Science

Post date: 04 Aug 2016
Covers the fundamentals of R programming, using the same material developed as part of the industry-leading Johns Hopkins Data Science Specialization.
Author(s): Roger D. Peng
Publication date: 03 Aug 2016
Document Type: Book
Tags: Big Data Data Science R Statistics


Statistical inference for data science : A companion to the Coursera Statistical Inference Course

Post date: 24 Oct 2016
This book gives a brief, but rigorous, treatment of statistical inference intended for practicing Data Scientists.
Author(s): Brian Caffo
Publication date: 24 May 2016
License: Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International
Document Type: Book
Tags: Data Science Statistics
 
Statistical inference for data science : A companion to the Coursera Statistical Inference Course

Statistical inference for data science : A companion to the Coursera Statistical Inference Course

Post date: 24 Oct 2016
This book gives a brief, but rigorous, treatment of statistical inference intended for practicing Data Scientists.
Author(s): Brian Caffo
Publication date: 24 May 2016
License: Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International
Document Type: Book
Tags: Data Science Statistics


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