Introduction to Machine Learning Workshop

SIAM Geosciences 2015
Machine Learning Workshop   

Schedule

  • Bottled drinks and snacks will be provided for workshop participants. 
  • Food/coffee is available for purchase at Tressider Union (map) or Stanford Bookstore Cafe (map).

Instructors
  • Alexander Ioannidis:  ioannidis [at] stanford [dot] edu 
  • Karianne Bergen:  kbergen [at] stanford [dot] edu
(Please send any emails to both instructors and include "ML Workshop" in subject heading)


About this Workshop

In this Introduction to Machine Learning Workshop, we will present the principles behind when, why, and how to apply modern machine learning algorithms. We introduce a framework for reasoning about how to apply various machine learning techniques. Topics will include: supervised and unsupervised methods, considerations of over-fitting/under-fitting (including regularization methods), considerations of interpretability, and techniques for handling missing data. 

This workshop is an abridged 'teaser' version of CME 250, a short course offered for credit at Stanford University; CME 250 will be offered again in Fall quarter 2015.

Prerequisites

The workshop assumes no prior background in machine learning. Previous exposure to undergraduate-level mathematics (calculus, linear algebra, statistics) and basic programming (e.g. R/Matlab/Python) will be particularly helpful.