Book Library - ComplexNetTSP/ComplexNetWiki GitHub Wiki
- Science Research Writing For Non-Native Speakers Of English, Hilary Glasman-Deal, 2009.
- Social Network Analysis for Startups, Maksim Tsvetovat and Alexander Kouznetsov, 2011.
- Statistics, Data Mining, and Machine Learning in Astronomy, Željko Ivezic ́et al, 2014.
- Real computing make Real, Forman S. Acton, 1996.
- Think Bayes: Bayesian Statistics in Python, 2013 (FREE)
- Python for Data Analysis, Wes McKinney, 2013.
- Python Cookbook, David Beazley and Brian K. Jones, 2013.
- Network Science: Theory and Application, Ted G. Lewis, 2014.
- Machine Learning for Hackers, Drew Conway and John Myles White, 2012.
- Algorithm Design, Jon Kleinberg, Eva Tardos, 2005.
- Pattern Recognition and Machine Learning, Christopher M. Bishop, 2006.
- Probabilistic Programming & Bayesian Methods for Hackers
- Scopatz and Huff, Effective Computation in Physics, 2015.
- Effective Python: 59 Specific Ways to Write Better Python, Brett Slatkin, 2015.
- Introduction to the Modeling and Analysis of Complex Systems, Hiroki Sayama, 2015 (FREE)
- Python for Finance Analyze Big Financial Data, Yves Hilpisch, O'Reilly 2014
- The Boost Graph Tutorial (FREE)
- Data Science from Scratch First Principles with Python, Joel Grus, 2015
- Introduction to Programming in Python, Robert Sedgewick, Kevin Wayne, Robert Dondero
- A Guide to Temporal Networks
- Python Data Science Handbook
- Introduction to Linear Algebra (Gilbert Strang)
- Hands-On Machine Learning with Scikit-Learn and TensorFlow (Aurélien Géron)
- Visualization Analysis & Design, 2014
- Fundamentals of Data Visualization, Claus O. Wilke
- Epidemic on Networks
- Statistical Rethinking
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