Collection of Data Science

A collection of Data Science Interview Questions Solved in Python and Spark: Hands-on Big Data and Machine Learning

Antonio Gulli, "A collection of Data Science Interview Questions Solved in Python and Spark: Hands-on Big Data and Machine Learning"
English | ISBN: 1517216710 | 2015 | 84 pages | EPUB | 1 MB

The Art of Data Science: A Guide for Anyone Who Works with Data  eBooks & eLearning

Posted by Grev27 at Feb. 1, 2016
The Art of Data Science: A Guide for Anyone Who Works with Data

Roger D. Peng, Elizabeth Matsui, "The Art of Data Science: A Guide for Anyone Who Works with Data"
English | ISBN: n/a | 2015 | PDF | 162 pages | 3,2 MB

Collection of popular science texts  eBooks & eLearning

Posted by stephan89 at Nov. 15, 2015
Collection of popular science texts

Collection of popular science texts
English | 409 Files | PDF-DJVU | 2.6 Gb
Small Doses of the Future: A Collection of Medical Science Fiction Stories (Science and Fiction) (Repost)

Small Doses of the Future: A Collection of Medical Science Fiction Stories (Science and Fiction) By Brad Aiken
2014 | 208 Pages | ISBN: 3319042521 | PDF | 2 MB
Small Doses of the Future: A Collection of Medical Science Fiction Stories (Science and Fiction) (Repost)

Small Doses of the Future: A Collection of Medical Science Fiction Stories (Science and Fiction) By Brad Aiken
2014 | 208 Pages | ISBN: 3319042521 | PDF | 4 MB
Small Doses of the Future: A Collection of Medical Science Fiction Stories (Science and Fiction)

Small Doses of the Future: A Collection of Medical Science Fiction Stories (Science and Fiction) By Brad Aiken
2014 | 208 Pages | ISBN: 3319042521 | PDF | 2 MB

Data Science with R  eBooks & eLearning

Posted by naag at Oct. 30, 2016
Data Science with R

Data Science with R
MP4 | Video: AVC 1280x720 | Audio: AAC 44KHz 2ch | Duration: 2.5 Hours | 418 MB
Genre: eLearning | Language: English

Data science is becoming more and more valuable to the workplace and to the global economy. Learn how to use the practice of data science and the programming language R to transform your data into actionable insight.

Intelligent Techniques for Data Science  eBooks & eLearning

Posted by Underaglassmoon at Oct. 19, 2016
Intelligent Techniques for Data Science

Intelligent Techniques for Data Science
Springer | Computer Science | Oct. 12 2016 | ISBN-10: 3319292056 | 272 pages | pdf | 7.08 mb

Authors: Akerkar, Rajendra, Sajja, Priti Srinivas
Focuses on methods significantly beneficial in data science, and clearly describes them at an introductory level, with extensions to selected intermediate and advanced techniques
Reinforces the machine learning principles with necessary demonstrations in the field of data science
Integrates illustrations, cases and examples to support pedagogical exposition
Equips readers with the necessary information to obtain hands‐on experience of data science

Mastering Python for Data Science [Repost]  eBooks & eLearning

Posted by mapusi at May 2, 2016
Mastering Python for Data Science [Repost]

Mastering Python for Data Science by Samir
English | 31 Aug. 2015 | ISBN: 1784390151 | 294 Pages | EPUB/MOBI/PDF (True) | 30.1 MB

If you are a Python developer who wants to master the world of data science then this book is for you. Some knowledge of data science is assumed.

Coursera - Introduction to Data Science  

Posted by house23 at Feb. 16, 2016
Coursera - Introduction to Data Science

Coursera - Introduction to Data Science
MP4 | AVC 88kbps | English | 960x540 | 30fps | 16h 03mins | AAC stereo 113kbps | 3.88 GB
Genre: Video Training

Commerce and research is being transformed by data-driven discovery and prediction. Skills required for data analytics at massive levels – scalable data management on and off the cloud, parallel algorithms, statistical modeling, and proficiency with a complex ecosystem of tools and platforms – span a variety of disciplines and are not easy to obtain through conventional curricula. Tour the basic techniques of data science, including both SQL and NoSQL solutions for massive data management (e.g., MapReduce and contemporaries), algorithms for data mining (e.g., clustering and association rule mining), and basic statistical modeling (e.g., linear and non-linear regression).