Machine Learning Crash Course
and Workshop
School of Mathematics
Georgia Institute of Technology

December 2019
Organizers: Heinrich Matzinger & Greg Mayer


Registration is free. Please email Dr. Matzinger, to receive a preparation package for the mandatory preparation exercises in Python (about 3 hours).


The workshop contains talks on results from high-dimensional statistics and machine learning which are relevant to practitioners. It also contains a mini Machine Learning crash course on Thursday and Friday, based on real data intuition and mathematics. Crash course sessions are mixed with hands on programming with Python, Numpy, Pytorch, Fastai. Those already familiar with Machine Learning can join us on Saturday and skip the Thursday and Friday sessions. 


Thur Dec 5 – Skiles 156

Fri Dec 6 – Skiles 257

Files for hands-on programming:

EM Slides: EM.pdf

  • 1100-1130 Welcome and introduction.Heinrich Matzinger and Greg Mayer
  • 1130-1230 Numpy programming hands on. Heinrich Matzinger and Greg Mayer
  • 1230-1300 Lunch
  • 13-14 Intro to intuitive regression, EM, Principal Components, text classification. Heinrich Matzinger
  • 14-16 Hands on project programming. Heinrich Matzinger and Greg Mayer
  • Hidden Markov Models Part 1: ett-Atlanta19

Sat Dec 7 – Skiles 268

  • 1100-1200 Data compression with random matrices. Konstantin Tikomirov, Georgia Tech
  • 1200-1230 Lunch
  • 1230-1330 Hidden Markov Models. Jurl Lember, Tartu University, Estonia
  • 1330-1430 Exploring low-dimensional structures in data science. Wenjin Liao
  • 1430-1530 Distributed SVD. Raphael Hauser, Oxford University
  • 1530-1630 The differential equation method: dynamic concentration Warnke Lutz, Georgia Tech
  • 1630-1900 Deep Learning with and/or Programming Deep net with fastai. Heinrich Matzinger

Sun Dec 8 – Skiles 268

  • 1100-1200 Deep learning with fastai, part II and programming. Heinrich Matzinger & Greg Mayer
  • 1200-1230 Lunch
  • 1230-1500 TBD