Machine Learning Fundamentals

Machine Learning Fundamentals

Course
en
English
80 h
This content is rated 3.9167 out of 5
Source
  • From edx.org
Conditions
  • Self-paced
  • Free Access
  • Fee-based Certificate
More info
  • 10 Sequences
  • Introductive Level
  • Starts on March 25, 2024
  • Ends on July 11, 2024

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Course details

Syllabus

  • Classification, regression, and conditional probability estimation
  • Generative and discriminative models
  • Linear models and extensions to nonlinearity using kernel methods
  • Ensemble methods: boosting, bagging, random forests
  • Representation learning: clustering, dimensionality reduction, autoencoders, deep nets

Prerequisite

  1. The previous courses in the MicroMasters program: and
  2. Undergraduate level education in:
    • Multivariate calculus
    • Linear algebra

Instructors

Sanjoy Dasgupta
Professor of Computer Science and Engineering
UC San Diego

Editor

The University of California, San Diego

Platform

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