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University of Beira Interior
MACHINE LEARNING
FACULTY
09/02/2024: The marks of the Exam (Recurso) are available. Tests can be seen on Friday, 10/02, 14:00-16:00.
25/01/2024: The marks of the Exam (Normal) are available. Tests can be seen on Friday, 26/01, 14:00-16:00.
10/01/2024: The marks of the written test and of the practical works are available. Tests can be seen on Thursday, 11/01, 14:00-16:00.
14/09/2023: The webpage for the course is online.
1. Introduction;
2. Model Representation, Linear Regression;
3. Logistic Regresion;
4. Dimensionality Reduction;
5. Neural Networks;
6. Support Vector Machines;
7. Unsupervised Classification;
8. Density Estimation;
9. Reinforcement Learning;
- C. Bishop. Pattern Recognition and Machine Learning, Springer, ISBN-13: 978-0387310732, 2011.
- M. Mohri, A. Rostamizadeh, A. Talwalkar, F. Bach. Foundations of Machine Learning, ISBN-13: 978-0262039406, 2018.
- Assiduity (A) To get approved at this course, students should attend to - at least - 80% of the theoretical and practical classes.
- Practical Projects (P) The practical projects of this course weight 50% (10/20) of the final mark.
- (P1) Practical Project 1: Supervised Learning (Linear Regression) (5/20).
- Due Date: Monday, October 10th, 2023, 23:59:59.
- (P2) Practical Project 2: Supervised Learning (Classification) (5/20).
- Due Date: Monday, October 31st, 2023, 23:59:59.
- (P3) Practical Project 3: Convolutional Neural Networks - CNNs (5/20).
- Due Date: Monday, November 28th, 2023, 23:59:59.
- (P4) Practical Project 4: Unsupervised Learning (5/20).
- Due Date: Monday, December 19th, 2023, 23:59:59.
- To get approved at the course, a minimal mark of 8/20 should be obtained in the practical project part.
- Written Test (F) Tuesday, January 9th, 2024, 14:00, Room 6.18.
- Mark (M) M = [A >= 0.8] * (P * 10/20 + F * 10/20).
- Admission to Exams Students with M >= 6 are admitted to final exams.
- The practical projects mark is considered in all examination epochs.