Session 5
Language processing: semantic analysis
Session 6
Speech processing: understanding and generating
Session 7
Classic computer vision with OpenCV: image processing
Session 8
Classic computer vision with OpenCV: parametric models
Session 9
ML: overview. Pipeline, testing, parameters, overfitting, ...
Session 10
ML: models and algorithms overview. kNN, SVM, ANN, ...
Session 11
ML: regression. Solving ranking and recommendation problems
Session 12
ML: clustering. Clustering quality metrics
COURSE OUTLINESession 3
Reasoning. Production systems and Bayesian networks
Session 4
Language processing: syntactic analysis
Session 2
AI as a function: algorithms of AI (search algorithms, A*, minimax, …)
Session 1
AI history and perception. Implementing simple intelligent agent
Session 13
ML: classification and embedding
Session 14
ML: Classification for computer vision. Image classifiers and detectors with SIFT, ANN etc.
Session 15
Selected topics (Hidden Markov Model*)