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.