Topic: Mathematics of Data Science

Other topics (to be covered if time is available and based on interest): Random graphs and network models; Algorithms for massive data sets and space-efficient data structures, Convex optimisation, Clustering.

Background required: graph theory, linear algebra.

- Kannan and Hopcroft's book draft, Chapters 2, 3 and maybe 7. Download here.

Download revised version of chapter 2 here. - D. A. Levin, Y. Peres, and E. Wilmer,
*Markov Chains and Mixing Times*, relevant chapters to be announced. Download here. - The proof of the Perron-Frobenius theorem presented in class is from Chapter 9 of the book
*Dynamical Systems*by Shlomo Sternberg (2010, Dover Publications, ISBN-13: 978-0486477053). The entire book can be downloaded at this link.

- Linear algrebra can be refreshed from Andrei Antonenko's course notes. Available here (local download only).
- Graph theory can be reviewed from Reinhard Diestel's book. Available here as an ebook.

- The volume of high dimensional solids. Handwritten lecture notes. 25th January 2016. Download here.

- Minor 1. Download tex template here (local access only). Posted 30th January 2016.
**Due: 11:55PM, 7th February 2016**. - Self study test 1. Download tex template here (local access only). Posted 8th February 2016.
**Due: 11:55PM, 29th February 2016**. - Minor 2. Download tex template here (local access only). Posted 7th March 2016.
**Due: 11:55PM, 13th March 2016**. - Minor 3. Download tex template here (local access only). Posted 31st March 2016.
**Due: 11:55PM, 5th April 2016**. - Minor 4. Download tex template here (local access only). Posted 19th April 2016.
**Due: 11:55PM, 2nd May 2016**.

**Latex only**. All exams are to be submitted as a pdf file created from latex source. No handwritten exams will be accepted.**Moodle submission only**. If you are registered in this course you are registered in this course on moodle. Please**only**submit your exam there the the appropriate upload link. If you are**not**registered in the course and wish to submit the exam you may email it to the TA Guntash Arora with cc to me.**Collaboratation and Plagiarism**- You are expected to attempt all problems on your own.
- You may consult online resources. However if you find the solution
to one of the problems online you are expected to
**not**look at the solution. - You may discuss solution ideas. However if you have the entire
solution it is incumbent on you to
**not**reveal the solution to your fellow students. - You may
**not**copy or cut and paste any text from any source whatsoever (your friends, the textbook, online, anything). - If you need to quote anything from anywhere a complete citation should be provided, i.e., it should be possible for the grader to look up the source easily.
- A violation of the copying rule (previous two bullet points) will lead to very stringent action with no excuse for even a minor-seeming violation and no opportunity to make up. This is an 800-level class and a high degree of integrity should beconsidered a prerequisite.

Amitabha Bagchi