Free Data Science eBooks - April 2017
Every month we scour the internet seeking out free eBooks to help you on your educational journey, and this month has been no different.
I hope these books prove to be a valuable resource to you and that you will visit regularly (and invite your friends too).
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This month, we have a book about Big Data, one about Data Science and one about Probability. They're all FREE, so go and fill your boots...
by Jeffrey Needham
Big data has more disruptive potential than any information technology developed in the past 40 years. As author Jeffrey Needham points out in this revealing book, big data can provide unprecedented visibility into the operational efficiency of enterprises and agencies.
Disruptive Possibilities provides an historically-informed overview 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. This relentlessly innovative form of computing will soon become standard practice for organizations of any size attempting to derive insight from the tsunami of data engulfing them.
Replacing legacy silos – whether they’re infrastructure, organizational, or vendor silos – with a platform-centric perspective is just one of the big stories of big data. To reap maximum value from the myriad forms of data, organizations and vendors will have to adopt highly collaborative habits and methodologies.
by Bryan Caffo, Robert D. Peng and Jeffrey Leek
In this concise book you will learn what you need to know to begin assembling and leading a data science enterprise, even if you have never worked in data science before.
You’ll get a crash course in data science so that you’ll be conversant in the field and understand your role as a leader. You’ll also learn how to recruit, assemble, evaluate, and develop a team with complementary skill sets and roles.
You’ll learn the structure of the data science pipeline, the goals of each stage, and how to keep your team on target throughout.
Finally, you’ll learn some down-to-earth practical skills that will help you overcome the common challenges that frequently derail data science projects.
by Charles M. Grinstead and J. Laurie Snell
This text is designed for an introductory probability course at the university level for undergraduates in mathematics, the physical and social sciences, engineering, and computer science.
It presents a thorough treatment of probability ideas and techniques necessary for a firm understanding of the subject. The text is also recommended for use in discrete probability courses. The material is organized so that the discrete and continuous probability discussions are presented in a separate, but parallel, manner.
This organization does not over emphasize an overly rigorous or formal view of probability and therefore offers some strong pedagogical value. Hence, the discrete discussions can sometimes serve to motivate the more abstract continuous probability discussions.
Practical Data Cleaning is now FREE...
(and accompanied by a FREE video course)
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