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Machine Learning

Organisation

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

Content
Lab Description Lab Materials Code Training
Data
Test
Data
1 Introduction details lab1.py - -
2 Linear Algebra details lab2.py - -
3 Linear Regression details linear_regression_ro.py ex3x.txt, ex3y.txt -
4 Logistic Regression details logistic_regression_ro.py, mapfeature.py, normalize_features.py ex4x.txt, ex4y.txt -
5 Naive Bayes details naive_bayes_ro.py train-labels.txt,train-features-full.txt test-labels.txt,test-features-full.txt
6 Neural Networks Representation details lab6.py - -
7 Neural Networks Learning details lab7.py nand_sum.txt nand_sum_test.txt
8 Convolutional Neural Networks details tfmnist.py train-images-idx3-ubyte.gz, train-labels-idx1-ubyte.gz t10k-images-idx3-ubyte.gz, t10k-labels-idx1-ubyte.gz
9 Clustering details k_means_ro.py lab09-data.txt lab09-data-test.txt
10 Principle Component Analysis details pca_ro.py - -
Examination

Written and practical exam at the end of the semester.