Apr 15, 2024  
2021-2022 Cal State East Bay Catalog 
    
2021-2022 Cal State East Bay Catalog [ARCHIVED CATALOG]

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CS 667 - Machine Learning


Units: 4
Introduction to machine learning with an emphasis on the underlying mathematics. Topics such as VC dimension, central limit theorem, gradient descent. Applications such as SVM and neural nets.

Prerequisites: MATH 230 and MATH 310; or M.S. Computer Science major.
Possible Instructional Methods: Entirely On-ground.
Grading: A-F grading only.
Cross-listed: MATH 667.
Student Learning Outcomes - Upon successful completion of this course students will be able to:
  1. Apply the fundamental definitions and theorems of data analysis.
  2. Apply techniques and algorithms of data analysis.




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