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Georgia Institute of Technology

Machine Learning

Georgia Institute of Technology and Brown University via Udacity


This class is offered as CS7641 at Georgia Tech where it is a part of the Online Masters Degree (OMS). Taking this course here will not earn credit towards the OMS degree.

Machine Learning is a graduate-level course covering the area of Artificial Intelligence concerned with computer programs that modify and improve their performance through experiences.

The first part of the course covers Supervised Learning, a machine learning task that makes it possible for your phone to recognize your voice, your email to filter spam, and for computers to learn a bunch of other cool stuff.

In part two, you will learn about Unsupervised Learning. Ever wonder how Netflix can predict what movies you'll like? Or how Amazon knows what you want to buy before you do? Such answers can be found in this section!

Finally, can we program machines to learn like humans? This Reinforcement Learning section will teach you the algorithms for designing self-learning agents like us!


  • Supervised Learning
    • Machine Learning is the ROX,Decision Trees,Regression and Classification,Neural Networks,Instance-Based Learning,Ensemble B&B,Kernel Methods and Support Vector Machines (SVM)s,Computational Learning Theory,VC Dimensions,Bayesian Learning,Bayesian Inference
  • Unsupervised Learning
    • Randomized optimization,Clustering,Feature Selection,Feature Transformation,Information Theory
  • Reinforcement Learning
    • Markov Decision Processes,Reinforcement Learning,Game Theory

Taught by

Michael Littman and Charles Isbell


4.4 rating, based on 7 Class Central reviews

Start your review of Machine Learning

  • Profile image for Jasmitha Kolamuri
    Jasmitha Kolamuri
    Course Review: "Machine Learning Fundamentals" I recently started taking the course "Machine Learning Fundamentals," and so far, it has been an enriching and insightful learning experience. This course provides a comprehensive introduction to the p…
  • Anonymous
    Superb course. At every step they probe how we should choose what to do next instead of just telling the steps.
  • An excellent overview of the field. The lectors are great, and I particularly liked the cross-references and similarities between different topics that they show.
  • Anonymous
    Poor delivery, outdated and barely an overview of machine learning algorithms. So watered down that there's very little meat (maths) left.
  • Rudolph Carpathian
  • Rubén Rangel
  • Amit Kumar

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