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Artificial Intelligence


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

Lab Description Materials
1 Linear Algebra details
2 Linear Regression details
3 Logistic Regression details
4 Naive Bayes details
5 Neural Networks: Representation details
6 Neural Networks: Gradients details
7 Neural Networks: BackPropagation details
8 Convolutional Neural Networks details
9 Clustering details
10 Principle Component Analysis details
Lab Description Lab Materials Code Training
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: Gradients details - -
8 Neural Networks: BackPropagation details lab8.py nand_sum.txt nand_sum_test.txt
9 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
10 Clustering details k_means_ro.py lab10-data.txt lab10-data-test.txt
11 Principle Component Analysis details pca_ro.py - -

Written and practical exam at the end of the semester.