Free Data Science eBooks - May 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 Data Scientists and the work that they do, one about probability and statistical modelling and one about machine learning. They're all FREE, so what are you waiting for...
by Harlan Harris, Sean Murphy and Marck Vaisman
Despite the excitement around "data science," "big data," and "analytics," the ambiguity of these terms has led to poor communication between data scientists and organizations seeking their help.
In this report, authors Harlan Harris, Sean Murphy, and Marck Vaisman examine their survey of several hundred data science practitioners in mid-2012, when they asked respondents how they viewed their skills, careers, and experiences with prospective employers.
The results are striking.
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by Norm Matloff
The materials here form a textbook for a course in mathematical probability and statistics for computer science students.
Computer science examples are used throughout, in areas such as: computer networks; data and text mining; computer security; remote sensing; computer performance evaluation; software engineering; data management; etc..
The R statistical/data manipulation language is used throughout. Since this is a computer science audience, a greater sophistication in programming can be assumed. It is recommended that the R tutorial, R for Programmers, be used as a supplement.
Throughout the units, mathematical theory and applications are interwoven, with a strong emphasis on modelling.
by Hal Daumé III
CIML is a set of introductory materials that covers most major aspects of modern machine learning (supervised learning, unsupervised learning, large margin methods, probabilistic modeling, learning theory, etc.).
Its focus is on broad applications with a rigorous backbone. A subset can be used for an undergraduate course; a graduate course could probably cover the entire material and then some.
If you're interested in learning more about the content in this blog post we've sought out the best blogs, books, video courses and other stuff from around the internet for you. Some may be free while others may not, and to help you decide we use the following ratings:
- FREE content
- costs less than 10 £/$/Euro
- costs less than 50 £/$/Euro
- costs less than 100 £/$/Euro
- costs more than 100 £/$/Euro
Disclosure: some of these resources may be affiliate links, and we may earn an affiliate commission for purchases you make when using these links
You can find further details in our TCs
Videos & Video Courses
4 hour Udemy Video Course delivered with animated videos. Perfect for beginners and will help get you started with basic statistical concepts
7 hour Udemy Video Course. Great for those needing a more business-oriented introduction to stats. Better still, the course even comes with homework. Yay!
9 hour Udemy Video Course. This is one of the top stats courses at Udemy and is a must-see for those that need to learn stats in R
CorrelViz - visualise all the correlations in your data in minutes
CorrelViz is completely automated and gives you the Story of Your Data in minutes, with one click - saving you months of manual analysis and shed-loads of cash!
Analyse all your data, discover all the correlations you seek - and some you never even dreamed of...
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