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Teaching GuideTerm Faculty of Computer Science |
Guía Provisional
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| Grao en Enxeñaría Informática |
 Subjects |
| Machine Learning |
| Contents |
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| Identifying Data | 2024/25 | |||||||||||||
| Subject | Machine Learning | Code | 614G01038 | |||||||||||
| Study programme |
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| Descriptors | Cycle | Period | Year | Type | Credits | |||||||||
| Graduate | 2nd four-month period |
Third | Optional | 6 | ||||||||||
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| Topic | Sub-topic |
| Introducción | Introduction to Machine Learning Learning Paradigms Inductive Learning No Free Lunch Theorems |
| Supervised Learning | Introduction Logistic Regression Support-Vector Machines Decision Trees Instant-Based Learning ML models for Regression Bayesian Learning Artificial Neural Networks Evaluation Ensembles |
| Deep Learning | Introduction Convolutional Networks Advanced models |
| Unsupervised Learning | Introduction Clustering Dimensionality reduction Rule Association Anomaly detection Unsupervised neural networks |
| Reinforcement Learning | Introduction Reinforcement theory Reinforcement learning algorithms Reinforcement learning applications |
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