The following is a list of free books (PDFs with data sets and codes) on R programming, Python and data science.

It provides a quick and practical guide to just about everything you can do with the open source R language and software environment. You’ll learn how to write R functions and use R packages to help you prepare, visualize, and analyze data.

It covers some of the most important modeling and prediction techniques, along with relevant applications. Topics include linear regression, classification, resampling methods, shrinkage approaches, tree-based methods, support vector machines, clustering, and more.

It helps you to learn R from the machine learning perspective. It introduces R-Weka package – Weka is another open source software used extensively in academic research.

It offers a highly accessible introduction to Natural Language Processing, the field that underpins a variety of language technologies ranging from predictive text and email filtering to automatic summarization and translation.

4. 75+ SAS Programming Tutorials

Please read the disclaimer about the Free Ebooks in this article at the bottom.

Free Ebooks on R, Python and Data Science |

**Free R Books with Data Sets****1. R in a Nutshell**

**2. Introduction to Statistical Learning with R**

It covers some of the most important modeling and prediction techniques, along with relevant applications. Topics include linear regression, classification, resampling methods, shrinkage approaches, tree-based methods, support vector machines, clustering, and more.

**Ebook :**Statistical Modeling with R

**3. Machine Learning with R**

It covers the most popular package of R on graphics ‘ggplot 2’. It covers the package in detail.

It covers topics on data preparation, data munging, data wrangling. It introduces a friendly interface IPython to code. In addition, it also covers NumPy and Pandas.

**Documentation and Data sets**

**Free Python Books with Data Sets****1. Python for Data Analysis**It covers topics on data preparation, data munging, data wrangling. It introduces a friendly interface IPython to code. In addition, it also covers NumPy and Pandas.

Ebook - Python for Data AnalysisEbook - Python for Data Analysis

**Datasets****Codes****2. Practical Data Science Codebook**
It covers a variety of situations with examples in the two most popular programming languages for data analysis - R and Python.

**Ebook - Practical Data Science Codebook****3. Text Processing in Python**
It is illustrative guide, which will walk you through all the text processing techniques in a step-by-step manner. It will demystify the advanced features of text analysis and text mining.

**Ebook - Text Processing in Python**

**4. Natural Language Processing with Python**It offers a highly accessible introduction to Natural Language Processing, the field that underpins a variety of language technologies ranging from predictive text and email filtering to automatic summarization and translation.

**Ebook - NLP with Python**

**Disclaimer :**

*Deepanshu Bhalla or ListenData has no affiliation to either the authors of the books or the web-sites hosting these PDF books shared in this post. We are not responsible for any content on other sites we link to. Most of the PDF links were gathered via Google search results in the first or second page and we assume they are hosted on either the authors' webpages or university sites. Please let me know if you think any PDF link posted is a copyright infringement, I will remove that link.*

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