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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.
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This month we highlight these 3 books:
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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!
