MTH594 Advanced data mining: theory and applications
The materials for the course MTH 594 Advanced data mining: theory and applications taught by Dmitry Efimov in American University of Sharjah, UAE in Spring, 2016 semester. The program of the course can be downloaded from the folder syllabus.
To compose this lectures mainly I used the ideas from three sources:
- Stanford lectures by Andrew Ng on YouTube: https://www.youtube.com/watch?v=UzxYlbK2c7E&list=PLA89DCFA6ADACE599
- The book "The elements of Statistical Learning" by T. Hastie, R. Tibshirani and J. Friedman: http://statweb.stanford.edu/~tibs/ElemStatLearn
- Lectures by Andrew Ng on Coursera: https://www.coursera.org/learn/machine-learning
All uploaded pdf lectures are adapted in a way to help students to understand the material.
The supplementary files from ipython folder are aimed to teach students how to use built-in methods to train the models on Python 2.7.
In case you found some mistakes or typos, please email me firstname.lastname@example.org, this course is a new for me and probably there are some :)
The content of the lectures: