The course is a basic introduction to machine learning, including:
Supervised learning (PAC learning, VC dimension, perceptron, SVM, stochastic gradient descent, deep learning, boosting, decision trees)
Unsupervised learning (principal component analysls, clustering, EM algorithm)
The course will include both theory and applied machine learning,
and a special emphasis will be put on machine learning algorithms.
The excercises will be done in Python; The course has large parts that are mathematical in nature.
מדעים מדויקים 0368-3235-01 מבוא ללמידה חישובית Introduction to Machine Learning שנה"ל תש"ף | סמ' ב' | פרופ גלוברזון אמיר