Best Free Online Documents, Books and Tutorials about R and Data Mining

Best Free Online Documents, Books and Tutorials about R and Data Mining under CC by

If you are looking for Document, Books Or Tutorials about  Data Mining and R programming to advance your Knowledge, here is the best  list in various formats available for free :

R Programming

Data Mining

  • Introduction to Data Mining by Pang-Ning Tan, Michael Steinbach and Vipin Kumar
    Lecture slides (in both PPT and PDF formats) and three sample Chapters on classification, association and clustering available at the above link.
  • Data Mining – Concepts and Techniques (3rd edition) by Jiawei Han, Micheline Kamber & Jian Pei
    Lecture slides in PPT format are provided for 13 chatpers.
  • Tutorial on Data Mining Algorithms by Ian Witten
  • Mining of Massive Datasets by Anand Rajaraman and Jeff Ullman
    The whole book and lecture slides are free and downloadable in PDF format.
  • Lecture notes of data mining course by Cosma Shalizi at CMU
    R code examples are provided in some lecture notes, and also in solutions to home works.
    It covers information retrieval, page rank, image search, information theory, categorization, clustering, transformations, principal components, factor analysis, nonlinear dimensionality reduction, regression, classification and regression trees, support vector machines, density estimation, mixture models, causal inference, etc.
  • Introduction to Information Retrieval by Christopher D. Manning, Prabhakar Raghavan and Hinrich Schütze at Stanford University
    It covers text classification, clustering, web search, link analysis, etc. The book and lecture slides are free and downloadable in PDF format.
  • Statistical Data Mining Tutorials by Andrew Moore
    Dozens of tutorial slides in PDF format
  • Tutorial on Spatial and Spatio-Temporal Data Mining
  • Tutorial on Discovering Multiple Clustering Solutions
  • Open-Source Tools for Data Mining
  • An overview of data mining tools

    Deep Learning

    Decision Trees and Random Forest

    Text Mining

  • Text Mining Tutorial
    It introduces various techniques at different levels of text processing, including word level, sentence level, document level and document-collection level. It covers stemming, stop words, document summarization, visualization, segmentation, categorization and clustering.
  • An introduction to text mining by Ian Witten
  • Slides for a tutorial on topic modeling by David M. Blei
  • A video from a talk on dynamic and correlated topic models

    Social Network Analysis and Graph Mining

    Association Rules

    Outlier Detection

    Sentiment Analysis


Data Mining with R

Classification/Prediction with R

Time Series Analysis with R

Association Rule Mining with R

Spatial Data Analysis with R

Text Mining with R

Social Network Analysis with R

Data Cleansing and Transformation with R

Case Studies with R

Big Data, MapReduce and Hadoop with R

Parallel Computing with R

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