A list of books covering Data Analysis, Data Science, Machine Learning, Data Visualization, Statistics & Associated Programming Languages

A collection of interviews with 16 of the world's most influential and innovative data scientists from across the spectrum of this hot new profession - from Yann LeCun at Facebook, to Daniel Tunkelang at LinkedIn, to Caitlin Smallwood at Netflix, to Jake Porway at DataKind and more ...

Street-Fighting Mathematics: The Art of Educated Guessing and Opportunistic Problem Solving

Data Driven: Profiting from Your Most Important Business Asset

Competing on Analytics: The New Science of Winning

Data Analysis with Open Source Tools


Who's #1?: The Science of Rating and Ranking

Doing Data Science: Straight Talk from the Frontline

Data Smart: Using Data Science to Transform Information into Insight

Data Science for Business:
What you need to know about data mining and data-analytic thinking

An Introduction to Statistical Learning: with Applications in R

Data Analysis Using Regression and Multilevel/Hierarchical Models

Statistics As Principled Argument

A Handbook of Statistical Analyses Using R, Second Edition

Mathematical Statistics and Data Analysis (with CD Data Sets)

Pattern Recognition and Machine Learning

Bayesian Reasoning and Machine Learning

Machine Learning: A Probabilistic Perspective

The LION Way: Learning plus Intelligent Optimization

Speech and Language Processing, 2nd Edition

Foundations of Statistical Natural Language Processing

Natural Language Processing with Python

Graph-based Natural Language Processing and Information Retrieval


Visualizing Data: Exploring & Explaining Data with Processing Environment

The Visual Display of Quantitative Information


Data-Intensive Text Processing with MapReduce

Data Mining with R: Learning with Case Studies

The Art of R Programming: A Tour of Statistical Software Design


Python for Data Analysis: Data Wrangling with Pandas, NumPy, and IPython


Learning Spark: Lightning-fast big data analytics

Fast Data Processing with Spark



Practical Cassandra: A Developer's Approach
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