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Machine Learning with MATLAB

Location: Tigard, OR
Venue: Embassy Suites Portland - Washington Square
Date: September 17, 2014
Time: 9:00 a.m. - 12:00 p.m.


Machine learning techniques are often used for analysis and decision-making tasks such as forecasting, pattern recognition, and data mining. However, implementing and comparing machine learning techniques to choose the best approach can be challenging.

In this free seminar, 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
  • Neural Networks
  • Decision trees and ensemble learning
  • Naïve Bayes Classification
  • Linear, logistic and nonlinear regression


Time Title
8:30 AM Registration and Continental Breakfast
9:00 AM Introduction to MATLAB for Machine Learning
9:30 AM Unsupervised Learning: Clustering and Data Mining

This section uses a human activity recognition example to demonstrate finding patterns in unlabeled data using various clustering techniques.
10:30 AM Break
10:45 AM Supervised Learning: Regression and Classification

Continuing with the previous example, this section demonstrates applying supervised learning techniques to train, test, refine and compare multiple classifiers.
11:30 AM Q&A and Next Steps
12:00 PM Conclusion of the Seminar
Machine Learning with MATLAB

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