A book list on data and sns

It』s nice to share knowledge on books to help others save time. Therefore I just went through my books on Goodreads quickly and hope to provide a quick summary of books I』ve read or glanced through that are related to 「data science」.

Let me know your list by commenting freely!

Introduction to Computation and Programming Using Python - 5/5 - A great starting point for Python, also a companion book for one of the earliest EDx open course on Python (search for the author』s name and you』ll find the free course online).

The Guru』s Guide to Transact-SQL - 5/5 - The milestone book for me to get into the world of SQL. Unfortunately not too relevant outside the world of SQL Server.

Social and Economic Networks - 5/5 - The best book I』ve found so far on social network thingies (even if just for jargons). Forever a reference.

Advanced R - 5/5 - bible for any adventurous R users. Welcome to the Hadley-universe.

Python Tutorial - 5/5 - Just to get started with Python.

Thinking, Fast and Slow - 5/5 - The best behavioral science book I』ve ever seen (yeah, I』ve read a lot in that field, admittedly and shamefully). Mike Develin said this is a book for data science. I agree.

An Introduction to Statistical Learning: With Applications in R - 5/5 - A quick read on both statistical learning and R.

Applied Predictive Modeling - 5/5 - A very, very handy book to get started with using R for modeling and machine learning.

Natural Language Process with Python - 5/5 - A quick read to grasp what』s offered in nltk package of Python.

Training Kit (Exam 70-461) - 5/5 - For SQL Server only. And it was great.

Interactive Data Visualization for the Web - 5/5 - For a time when I was hooked with D3. Ah all those memories.

Machine Learning (by Tom Mitchell) - 5/5 - A classic on machine learning theories. A bit outdated.

IBM SPSS Modeler Cookbook - 5/5 - Pretty much the only reasonable handbook for SPSS Modeler. But not so relevant if you are not using this tool. Here』s a nice quote from this book.

The Grammar of Graphics - 5/5 - The 「secrets」 behind ggplot2. Or, the secrets behind any grammatical thinking of lots of Hadley-universe-thingies.

Practical Data Science with R - 4/5 - The authors have a website that』s worth recommending http://www.win-vector.com/blog/. The book is fairly written with lots of R scripts for copying and pasting purposes.

Data Analysis Using SQL and Excel - 4/5 - A good get-to-start book for data analysis. Only good for quick glancing.

A bunch other stuff written by Stephen Few or Tufte. But I honestly think they are not in par with the great ancestor of data visualization, Semiology of Graphics.

On top of this, there are a bunch of books by Kimball on data warehousing that will be helpful for base-lining data warehousing concepts. Also, papers on data normalization. NoSQL data structures such as Seven Databases in Seven Weeks.
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