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Introduction to Machine Learning

Machine learning refers to the use of computational tools and statistical learning to understand complex datasets. The goal of most machine learning methods is to identify patterns in the data that can be used to make highly accurate predictions of an outcome or to accurately classify items into categories. This workshop will provide an introduction to the practice of machine learning, the most common models, and their implementation.

Topics include:

  • Data exploration and visualization
  • Supervised learning methods
  • Unsupervised learning methods
  • Implementation
  • Model evaluation

Fee: None to members of the Cornell community, but registration is required. Since space is limited, early registration is encouraged.

For times and locations of upcoming workshops, please see the Workshop Schedule.