Machine Learning

Organisation

Bachelor: 2h/week course and 2h/week laboratory, Summer semester
Lecturer: Sorin Grigorescu
Laboratory: Cosmin Ginerica, Bogdan Trasnea
Language: Romanian

Laboratory work

Lab Description Lab Materials Source Code Training Data
1 Python introduction details lab1.py
2 Linear algebra in Python details lab2.py
3 Linear regression details linear_regression_ro.py ex3x.txt, ex3y.txt
4 Logistic regression details linear_regression_ro.py, mapfeature.py, normalize_features.py ex4x.txt, ex4y.txt
5 Naive Bayes Classifier details naive_bayes_ro.py test-features-full.txt test-labels.txt train-features-full.txt train-labels.txt
6 Neural Networks: Representation details lab6.py
7 Neural Networks: Training details lab7.py nand_sum.txt, nand_sum_test.txt
8 Convolutional Neural Networks details tfmnist.py
9 Clustering details k_means_ro.py lab9-data.txt, lab9-data-test.txt
10 Principal Component Analysis details pca_ro.py

Examination

Written and practical exam at the end of the semester.