Here are the list of the books I have read. I give each book a score and in some cases write a short comment. My scores are out of 5 where 5 is the best possible score and 1 is the worst.
- 2030 – Albert Brooks (1)
- The Lost Symbol – Dan Brown (5)
- Digital Fortress – Dan Brown (3)
- Angels and Demons – Dan Brown (5)
- A Theorist Toolkit – Sanjeev Arora (5): A short course introducing dome useful tools.
- Stochastic Geometry for Wireless Networks – Martin Haenggi (4)
- Concentration of Measure for the Analysis of Randomized Algorithm – Devdatt Dubhashi and Alessandro Panconesi (5): I truly enjoyed reading this book and found the tools introduced in there useful. Highly Suggest reading it.
- The Probabilistic Method – Noga Alon (5)
- Think Stats (4): Introduction to probability and statistics in Python.
- Dimension Reduction: A Guided Tour – Christopher J. C. Burges (1): The book has many errors and is not written well. Do not recommend it.
- Nonlinear Dimensionality Reduction – John A. Lee and Michel Verleysen (4): Really a good book on DR with insightful examples.
- The Elements of Statistical Learning – Hastie, Tibshirani, and Friedman (5): One of the best books on the subject.
- Learning Deep Architectures for AI - Bengio (5): Definitely recommend this book.