Assignments for the Machine Learning bachelor course @ USI SP 23
This repository contains the assignments for the Machine Learning Bachelor Course for the Spring 2023 semester.
Course director: Alippi Cesare
Assistants:
- Adorni Giorgia
- Ezzeddine Fatima
- Manenti Alessandro
The assignments will cover various topics related to machine learning, including supervised and unsupervised learning, deep learning, and model performance assessment. Specific topics include linear and nonlinear models for regression and prediction, statistical theory of learning, feature extraction and model selection, autoencoders, convolutional neural networks, k-means clustering, fuzzy C-means, principal component analysis, and more.
The objective of the assignments is to help students reinforce their understanding of the course material and develop their skills in designing and implementing machine learning solutions. Assignments will be due on specific dates, and students must submit their solutions on time.
Each assignment will be provided as a separate folder in the repository. The specific instructions and guidelines for each assignment can be found in the corresponding folder's README file. Students must follow the instructions carefully and submit their solutions as instructed.
Students are not permitted to share their solutions or code with others. Any attempt to cheat will result in disciplinary action.
If you have any questions or concerns about the assignments or the code files, please post your questions on the course Q&A forum, or contact the course teaching assistants directly.
Good luck with the assignments!