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October 1, 2020

Free Data Science eBooks – October 2020

Looking for FREE Data Science books? Then you're in the right place.

Every month we feature 3 of the best free books on a variety of Data Science topics, from programming in R and Python to Statistics, Machine Learning and lots more.

These free books might be time limited (or not), and you'll find them in a variety of formats, from both top-tier publishers and self-published authors.

If you want to be the first to know when our monthly free books post is out, subscribe to our newsletter - we have a huge back-catalogue of titles for you to browse through!

This month we highlight these 3 books:

  • Object Oriented Programming With Python
  • Computer Age Statistical Inference
  • Statistical Learning with Sparsity

They're all FREE, so help yourselves...

More...

Disclosure: The FREE ebooks were free to download at the time of posting but other links in this post may contain affiliate links. As Amazon Associates we may earn from qualifying purchases.

​​You can find further details in our TCs

Free Data Science Books for October

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Ashwin Pajankar and Sushant Garg

This book is the simple and definitive guide to the Python 3 Object Oriented Programming. Other book of the similar genres make use of complicated writing style and examples to introduce the readers to the OOP in Python 3. However, this book uses Simple language to explain concepts. It is aimed at intermediate learners who already know Python.

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Bradley Efron and Trevor Hastie

This book takes us on a journey through the revolution in data analysis following the introduction of electronic computation in the 1950s. Beginning with classical inferential theories – Bayesian, frequentist, Fisherian – individual chapters take up a series of influential topics: survival analysis, logistic regression, empirical Bayes, the jackknife and bootstrap, random forests, neural networks, Markov chain Monte Carlo, inference after model selection, and dozens more. The book integrates methodology and algorithms with statistical inference, and ends with speculation on the future direction of statistics and data science.

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Trevor Hastie, Robert Tibshirani and Martin Wainwright

During the past decade there has been an explosion in computation and information technology. With it has come vast amounts of data in a variety of fields such as medicine, biology, finance, and marketing. This book descibes the important ideas in these areas in a common conceptual framework.

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Related Udemy Video Courses

Below are a few related Udemy courses that we recommend. They are by no means the only ones - there are LOADS more, and if these don't tickle your fancy, just click through. I'm sure you'll find something that does.

*NOTE - the prices listed below are the full price, and are not automatically updated when a sale is on. If you want to find out the sale price (often around 10 £/$/Euro), just click through!

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Lee Baker is an award-winning software creator that lives behind a keyboard in a darkened room. Illuminated only by the light from his monitor, he aspires to finding the light switch. With decades of experience in science, statistics and artificial intelligence, he has a passion for telling stories with data, yet despite explaining it a dozen times, his mother still doesn’t understand what he does for a living. Insisting that data analysis is much simpler than we think it is, he creates friendly, easy-to-understand video courses that teach the fundamentals of data analysis and statistics. As the CEO of Chi-Squared Innovations, one day he’d like to retire to do something simpler, like crocodile wrestling.

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