Machine learning is a type of artificial intelligence (AI) that provides computers with the ability to learn without being explicitly programmed. This area is also concerned with issues both theoretical and practical.
In this course, we will present algorithms and approaches in such a way that grounds them in larger systems as you learn about a variety of topics, including:
statistical supervised and unsupervised learning methods
randomized search algorithms
Bayesian learning methods
The course also covers theoretical concepts such as inductive bias, the PAC and Mistake‐bound learning frameworks, minimum description length principle, and Ockham's Razor. In order to ground these methods the course includes some programming and involvement in a number of projects.
By the end of this course, you should have a strong understanding of machine learning so that you can pursue any further and more advanced learning.
This is a three-credit course.
Week 1: ML is the ROX/SL 1- Decision Trees
Week 2: SL 2- Regression and Classification
Week 3: SL 3- Neutral Networks
Week 4: SL 4- Instance Based Learning
Week 5: SL 5- Ensemble B&B
Week 6: SL 6- Kernel Methods & SVMs
Week 7: SL 7- Comp Learning Theory
Week 8: SL 8- VC Dimensions
Week 9: SL9- Bayesian Learning
Week 10: SL 10- Bayesian Inference
Week 11: UL 1- Randomized Optimization
Week 12: UL 2- Clustering/ UL 3- Feature Selection
Week 13: UL 4- Feature Transformation/UL 5- Info Theory
Week 14: RL 1- Markov Decision Processes
Week 15: Reinforcement Learning
Week 16: RL 3 Game Theory/Outro
MOOCs stand for Massive Open Online Courses. These arefree online courses from universities around the world (eg. StanfordHarvardMIT) offered to anyone with an internet connection.
How do I register?
To register for a course, click on "Go to Class" button on the course page. This will take you to the providers website where you can register for the course.
How do these MOOCs or free online courses work?
MOOCs are designed for an online audience, teaching primarily through short (5-20 min.) pre recorded video lectures, that you watch on weekly schedule when convenient for you. They also have student discussion forums, homework/assignments, and online quizzes or exams.