Learn Supervised, Unsupervised and Reinforcement Learning approaches from entertaining and competent instructors. Offered at Georgia Tech, this free and interactive course covers an interesting area of Artificial Intelligence.
Created by: Michael Littman
Produced in 2015
What you will learn
- Supervised Learning to understand how your phone can recognize your voice
- Algorithms that Netflix uses to accurately recommend movies
- Apply Reinforcement Learning to control robots or win a game of chess
- Kernel methods, including Support Vector Machines (SVM)
- Where and how to use Bayesian inference techniques
- Clustering, Feature transformation and selection
- Demystify Markov decision processes
- How do Machine Learning and Game Theory intersect
- Much, Much more!
- The course is a part of the Online Masters Degree at one of the best universities for computer science.
- Charming and entertaining instructors.
- Broad survey of the Machine Learning field.
- Unique style of teaching that will not suit everyone.
- Long and Time-consuming.
Michael L. Littman joined Brown University's Computer Science Department after ten years (including 3 as chair) at Rutgers University. His research in machine learning examines algorithms for decision making under uncertainty. Littman has earned multiple awards for teaching and his research has been recognized with three best-paper awards on the topics of meta-learning for computer crossword solving, complexity analysis of planning under uncertainty, and algorithms for efficient reinforcement learning. He has served on the editorial boards of the Journal of Machine Learning Research and the Journal of Artificial Intelligence Research. In 2013, he was general chair of the International Conference on Machine Learning (ICML) and program co-chair of the Association for the Advancement of Artificial Intelligence Conference and he served as program co-chair of ICML 2009.
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