About textbooks
This year, the course will not have one single textbook, but
will draw inspiration from a number of different textbooks. I've
listed the ones that I'm considering below. We will be making pdf
versions of the parts we're using available here as the course
progresses. Below, the books are divided into groups by topic. The
titles in bold are the central texts.
Machine Learning
- Programming Collective
Intelligence (O'Reilly 2007). Toby Segaran.
- Data Analysis with Open Source Tools (O'Reilly 2011). Philipp
K. Janert.
- Machine Learning for Hackers (O'Reilly 2012). Drew Conway and
John Myles White.
Network Analysis
- Networks, Crowds, and Markets. Reasoning about a Highly
Connected World (Cambridge University Press 2012).
David Easley and Jon Kleinberg. [Free
Online]
- Social Network Analysis for Startups (0'Reilly 2011). Maksim
Tsvetovat and Alexander Kouznetsov.
- Think Complexity (O'Reilly 2012). Allen B. Downey.
Data Analysis
- Python for Data Analysis (O'Reilly 2012). Wes McKinney.
- Think Stats (O'Reilly 2011). Allen B. Downey.
- Machine Learning for Hackers (O'Reilly 2012). Drew Conway and
John Myles White.
API's etc
- Mining the Social Web (O'Reilly 2011). Matthew A.
Russell
Natural Language Processing
- Natural Language Processing with Python (O'Reilly 2009).
Steven Bird, Ewan Klein, and Edward Loper. [Free
Online]
