James Cain, Manager - Experimental Learning Environments, OEIT
Enrollment: Register at link below:
Machine learning techniques are often used for data analysis and decision-making tasks such as forecasting, classification of risk, estimating probabilities of default, and data mining. However, implementing and comparing machine learning techniques to choose the best approach can be challenging. In this session, you will learn about several machine learning techniques available in MATLAB and how to quickly explore your data, evaluate machine learning algorithms, compare the results, and apply the best technique to your problem.
Highlights include unsupervised and supervised learning techniques such as:
-K-means and other clustering tools
-Decision trees and ensemble learning
-Naïve Bayes classification
-Linear, logistic, and nonlinear regression
MathWorks at MIT IAP 2014
MathWorks is hosting six sessions during MIT's Independent Activities Period (IAP) 2014. Join us to learn how you can use MATLAB and Simulink for technical computing and application development in engineering, math, and science. Attend as many sessions as you like.
Please visit the following URL for more information and to register for this session:
Sponsor(s): Office of Educational Innovation and Technology, Electrical Engineering and Computer Science
Contact: Tim Mathieu, Tim.Mathieu@mathworks.com