ICME Summer Workshop: Introduction to Machine Learning

Thursday, August 17, 2017

9:00 am

On the Stanford campus. Location will be shared with registrants.

Sponsored by:
School of Engineering

XCME006 - Introduction to Machine Learning

Overview

This workshop presents the basics behind the application of modern machine learning algorithms. We will discuss a framework for reasoning about when to apply various machine learning techniques, emphasizing questions of over-­fitting/under-­fitting, regularization, interpretability, supervised/unsupervised methods, and handling of missing data. The principles behind various algorithms—the why and how of using them—will be discussed, while some mathematical detail underlying the algorithms—including proofs—will not be discussed. Unsupervised machine learning algorithms presented will include k-­means clustering, principal component analysis (PCA), and independent component analysis (ICA). Supervised machine learning algorithms presented will include support vector machines (SVM), classification and regression trees (CART), boosting, bagging, and random forests. Imputation, the lasso, and cross-­validation concepts will also be covered. The R programming language will be used for examples, though participants need not have prior exposure to R.

Prerequisite: undergraduate-­level linear algebra and statistics; basic programming experience (R/Matlab/Python).

Topics Include

  • Basic Concepts and Intro to Supervised Learning: linear and logistic regression
  • Penalties, regularization, sparsity (lasso, ridge, and elastic net)
  • Unsupervised learning: clustering (k-­means and hierarchical) and dimensionality reduction (Principal Component Analysis, Independent Component Analysis, Self-­Organizing Maps, Multi-­Dimensional Scaling)
  • Unsupervised Learning: NMF and text classification (bag of words model)
  • Supervised Learning: loss functions, cross-­validation (bias variance trade-­off and learning curves), imputation (K-­nearest neighbors and SVD), imbalanced data
  • Classification and Regression Trees (CART)
  • Support Vector Machines (SVM) and Neural Nets
  • Ensemble methods (Boosting, Bagging, and Random Forests)

The ICME offers summer workshops to students, partners, and the wider community (first come first served, in that order). These day-long workshop happen from August 14-18, 2017, from 9:00am to 4:45 pm. To view other workshop descriptions, or to get general information about the ICME Summer Workshop Series, click here.

ICME Summer Workshops are open to participants 18 years and older. If you are under the age of 18 and would like to participate, please contact the program administrator

Important Notes:

  • Please note that these are not Stanford for-credit courses.
  • Stanford academic and non-academic staff may register under the 'Faculty' ticket type. 
  • Room locations, information on what to bring, and directions to campus will be provided to those who register in advance of each workshop.
  • These workshops are open to participants 18 years and older. If you are under the age of 18 and would like to participate, please inquire with icme-contact@stanford.edu
  • If you have questions, please contact the ICME via email icme-contact@stanford.edu

Questions? Please contact ICME 

When:
Thursday, August 17, 2017
9:00 am – 4:45 pm
Where:
On the Stanford campus. Location will be shared with registrants.
Admission:

Register here.

Tags:

Engineering Seminar 

Audience:
General Public, Students, Members
Contact:
(650)724-3313, icme_workshops@lists.stanford.ed
More info:
Visit this website