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Introduction to Machine Learning

COS 324

1254
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Provides a broad introduction to different machine learning paradigms and algorithms, providing a foundation for further study or independent work in machine learning, artificial intelligence, and data science. Topics include linear models for classification and regression, support vector machines, neural networks, clustering, principal components analysis, Markov decision processed, planning, and reinforcement learning. The goals of this course are three-fold: to understand the landscape of ML, how to compute the mathematics behind techniques, and how to use Python and relevant libraries to implement and use various methods.
Sections tab content

Section L01

Section P01

Section P01A

  • Type: Precept
  • Section: P01A
  • Status: C
  • Enrollment: 0
  • Capacity: 0
  • Class Number: 43083
  • Schedule: Th 10:00 AM-10:50 AM

Section P02

Section P02A

  • Type: Precept
  • Section: P02A
  • Status: C
  • Enrollment: 0
  • Capacity: 0
  • Class Number: 43084
  • Schedule: Th 11:00 AM-11:50 AM

Section P03

Section P04

Section P05

Section P06

Section P07

  • Type: Precept
  • Section: P07
  • Status: C
  • Enrollment: 0
  • Capacity: 0
  • Class Number: 40094
  • Schedule: Th 07:30 PM-08:20 PM