Jul 25, 2024  
2023-2024 Cal State East Bay Catalog 
2023-2024 Cal State East Bay Catalog [ARCHIVED CATALOG]

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STAT 652 - Statistical Learning

Units: 2
Statistical machine learning overview. Choosing a learning algorithm. Unsupervised learning including classification methods, nearest neighbors, naïve Bayes, decision trees and rules, neural networks, k-means. Supervised learning including linear regression and logistic regression. Model performance and evaluation. Confusion matrix. Report writing.

Prerequisites: Post-baccalaureate standing.
Possible Instructional Methods: On-ground, or Hybrid or Online-Asynchronous.
Grading: A-F grading only.
Course Typically Offered: Spring ONLY

Student Learning Outcomes - Upon successful completion of this course students will be able to:

  1. Use software to learn from data.
  2. Critically evaluate learning models.
  3. Extract data from large data source to learn from data.
  4. Create reproducible reports.

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