General information
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Official course description: DM587. (The course shares some classes with AI511.)
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Room in ItsLearning: DM587
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Teacher: Marco Chiarandini
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Teacher assistants: Casper Asbjørn Eriksen (DM587: H1, AI511 H9), Charalampos Evangelatos (AI511: H21, H8)
Schedule
- Semester overview: (, , )
Contents
Introductory Classes
| Week | Date | Topics and Slides | Suggested reading |
|---|---|---|---|
| 43 | Oct 21 | Python - Part 1a: basics, data types, control flow | App A, B and ch 1-3 of [HJ1]; [DB] |
| 43 | Oct 24 | Python - Part 1b: std library, OO progr. | App A, B and ch 1-3 of [HJ1]; [DB] |
| 44 | Oct 28 | Python - Part 2: exceptions, file i/o, numpy | Ch 4,6 of [HJ1]; [NS] |
| 44 | Oct 29 | Python - Part 3: graphics, data viz, pandas | Ch 5,8 of [HJ1]; Sc 6.3-6.5 of [AR]; (Ch 9 of [HJ2]) |
| 45 | Nov 4 | Least Squares Data Fitting | [MC]; Sc. 6.3-6.5 of [AR] |
| 46 | Nov 11 | Graph Isomorphism and Molecules | |
| 47 | Nov 18 | From Random Polygon to Ellipse | |
| 48 | Nov 25 | Page Rank | |
| 49 | Dec 2 | Principal Component Analysis and Eigenfaces | |
| 50 | Dec 9 | Linear Programming and Numerical Methods |
Exercises and Assignments
| Week | Sheet | Topic | Solutions | Assignments |
|---|---|---|---|---|
| 43 | colab1; sheet0; sheet1 | Python, Part 1 | sheet0; sheet1 | asg 0 |
| 44 | sheet2 | Python, Part 2 and 3 | sheet2 | asg 1 |
| 45 | sheet3 | Least Squares | asg2 |
References
Recommended book:
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[HJ1] Python Essentials. Jeffrey Humpherys and Tyler J. Jarvis, managing editors
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[HJ2] Data Science Essentials. Jeffrey Humpherys and Tyler J. Jarvis, managing editors
Other References:
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[DB] David Beazley. Python Tutorial Video
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[HJ] Jeffrey Humpherys and Tyler J. Jarvis. Foundations of Applied Mathematics. Volume 1. Mathematical Analysis. 2017. Society for Industrial and Applied Mathematics.
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[AR] Howard Anton and Chris Rorres. Elementary Linear Algebra With Supplemental Applications. Edition International Student Version. 11th Edition. 2014. Wiley
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[PK] Philip N. Klein. Coding the Matrix: Linear Algebra through Applications to Computer Science. 1st Edition. Newtonian Press; 1 edition, September 3, 2013
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[AH] Martin Anthony and Michele Harvey, Linear Algebra, Concepts and Methods. 2012. Cambridge
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[Le] Steven J. Leon, Linear Algebra with Applications, Prentice Hall (2010).
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[FSV] Computing with Python: An introduction to Python for science and engineering Claus Führer, Jan Erik Solem, Olivier Verdier
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[SAA] Immersive linear algebra by J. Ström, K. Åström, and T. Akenine-Möller. 2017.
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[MC] Lecture Notes on Linear Regression by Marco Chiarandini.
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[NS]
numpyAPI reference and its submodule linalg; andscipyAPI reference and its submodule linalg. (scipyis a superset ofnumpy.) -
[Wi] Introduction to Graph Theory, Robin J. Wilson, 5th edition, 2010.
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[BP] Brin, Sergey; Page, Lawrence. The anatomy of a large-scale hypertextual Web search engine. Computer Networks and ISDN Systems. Volume 30, Issues 1–7, April 1998, Pages 107-117
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[PBMW] Page, Lawrence; Brin, Sergey; Motwani, Rajeev and Winograd, Terry, The PageRank citation ranking: Bringing order to the Web. 1999
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[LM] Amy N. Langville; Carl D. Meyer. A Survey of Eigenvector Methods for Web Information Retrieval. SIAM Review, Society for Industrial and Applied Mathematics, Vol. 47, No. 1, pp. 135–161
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[V] Robert J. Vanderbei, Linear Programming: Foundations and Extensions, Fourth Edition, Springer. 2014.