הטכניון - מכון טכנולוגי לישראל Technion - Israel Institute of Technology Технион - израильский технологический институт ألتخنيون - معهد تكنولوجي لإسرائيل

02360756 - מבוא למערכות לומדות 02360756 - Introduction to Machine Learning 02360756 - Introduction to Machine Learning 02360756 - Introduction to Machine Learning

חורף 2019-2020Winter 2019-2020Зима 2019-2020شتاء 2019-2020

סילבוס Syllabus Силабус خطة الدورة

Here is the planned syllabus:

Lectures Calendar

	Subject
1	Introduction, Gentle start: online
2	Probability Review, Uniform Convergence Principle
3	PAC learning and VC theory
4	Nonuniform Learnability
5	Computational Complexity of Learning
6	SVM (support vector machine): geometric margin, norm regularization, representer theorem, kernel trick, sGD (sub gradient descent) and stochastic sGD for SVM
7	Kernels, Regularized Loss Minimization, Validation
8	learning guarantees for SGD, early stopping as regularization, online learning, online vs stochastic optimization
9	Feature selection
10	multilayer networks, learning input representations
11	Probabilistic models, Naive Bayes, generative vs discriminative models, MAP (maximum a posteriori) vs SRM (structural risk minimization)
12	Advanced topics
13	Advanced topics

Tutorials Calendar

	Subject
0	Intro
1	Offline Learning, Hoeffding Bound
2	VC dimension tutorial
3	Least Squares, Linear Programming, Perceptron
4	convex sets and functions, convex problems, GD (gradient descent), smoothness, lipschitz, newton, sub-gradient and sGD (sub gradient descent)
5	sub-gradients, sub-gradient descent for SVM
6	Not decided yet
7	Not decided yet
8	Not decided yet
9	Back-propagation
10	ML (maximum likelihood), MAP (maximum a posteriori), Bayesian estimates
11	Linear Discriminant Analysis (LDA) and other probabilistic models
12	Not decided yet