There should be one assignment per week, the last one being a group assignment (to work on a team of 4-5)
+ Bi-weekly 10 minutes quiz session

Jeff Edmonds Dept. EE and Computer Science York University Toronto Canada Email: jeff cse.yorku.ca Jeff teaches Theoretical Computer Science at all levels Practical Machine Learning: (Possible Teachers) Chester Wyke , Sarah Vollmer , Laily Ajellu , Pedram Ahadinejad , Oriana Quevedo

Computers can now drive cars and find cancer in x-rays. For better or worse, this will change the world (and the job market). Strangely designing these algorithms is not done by telling the computer what to do or even by understanding what the computer does. The computers learn themselves from lots and lots of data and lots of trial and error. This learning process is more analogous to how brains evolved over billions of years of learning. The machine itself is a neural network which models both the brain and silicon and-or-not circuits, both of which are great for computing. The only difference with neural networks is that what they compute is determined by weights and small changes in these weights give you small changes in the result of the computation. The process for finding an optimal setting of these weights is analogous to finding the bottom of a valley. "Gradient Decent" achieves this by using the local slope of the hill (derivatives) to direct the travel down the hill, i.e. small changes to the weights. There is some theory. If a machine is found that gives the correct answers on the randomly chosen training data without simply memorizing, then we can prove that with high probability this same machine will also work well on never seen before instances.

Jeff's Zoom, Recording 2022, Jeff's ML Chapter
Python/Labs
Machine Learning Content
Non-Machine Learning Theory
Request: Jeff tends to talk too fast. Please help him go pole pole slowly.