Free Data Science eBooks – May 2019

3 Free data science books for May

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:

  • Interpretable Machine Learning
  • Introduction to Data Science
  • ​Developing Data Products in R

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

More...

3 free data science books May 2019

Disclosure: The FREE ebooks are free to download 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

By Christoph Molnar

Interpretable Machine Learning

This book is about making machine learning models and their decisions interpretable.

After exploring the concepts of interpretability, you will learn about simple, interpretable models such as decision trees, decision rules and linear regression. Later chapters focus on general model-agnostic methods for interpreting black box models like feature importance and accumulated local effects and explaining individual predictions with Shapley values and LIME.

All interpretation methods are explained in depth and discussed critically. How do they work under the hood? What are their strengths and weaknesses? How can their outputs be interpreted? This book will enable you to select and correctly apply the interpretation method that is most suitable for your machine learning project.

The book focuses on machine learning models for tabular data (also called relational or structured data) and less on computer vision and natural language processing tasks. Reading the book is recommended for machine learning practitioners, data scientists, statisticians, and anyone else interested in making machine learning models interpretable.


​Related Udemy Video Courses

*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!


By Rafael A. Irizarry

Introduction to Data Science

The demand for skilled data science practitioners in industry, academia, and government is rapidly growing. This book introduces concepts and skills that can help you tackle real-world data analysis challenges. It covers concepts from probability, statistical inference, linear regression and machine learning. It also helps you develop skills such as R programming, data wrangling with dplyr, data visualization with ggplot2, algorithm building with caret, file organization with UNIX/Linux shell, version control with Git and GitHub, and reproducible document preparation with knitr and R markdown. The book is divided into six parts: R, Data Visualization, Data Wrangling, Probability, Inference and Regression with R, Machine Learning, and Productivity Tools. Each part has several chapters meant to be presented as one lecture. The book includes dozens of exercises distributed across most chapters. 


​Related Udemy Video Courses

*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!


By Brian Caffo and Sean Cross

Developing Data Products in R

This book covers the exciting field of data products. A data product is the output of a data science experiment. In this book we focus on developing data products in R, the most popular language for data scientists. Special emphasis is given to developing Shiny apps. Shiny is a platform for developing web front ends for back end R calculations. Shiny allows users to create polished web apps while only knowing R and a little bit of html. 

After shiny we cover other ways to make reproducible presentations and interactive graphics. In reproducible presentations, we cover Slidify and RStudio's Presenter. In interactive graphics, we demonstrate RCharts, Leaflet, googleVis and plot.ly.


​Related Udemy Video Courses

*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!


3 free data science books for May 3 free data science books for May
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