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2c7c9e58e0
Fixed bug in ROC curve visualization |
2 years ago | |
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| lod | 2 years ago | |
| ml1 | 2 years ago | |
| ml2 | 2 years ago | |
| ml3 | 5 years ago | |
| ml4 | 3 years ago | |
| ml5 | 3 years ago | |
| nlp | 3 years ago | |
| python | 2 years ago | |
| rdf | 4 years ago | |
| .gitignore | 8 years ago | |
| CONTRIBUTING.md | 5 years ago | |
| Makefile | 5 years ago | |
| README.md | 3 years ago | |
| logo.jpg | 6 years ago | |
| requirements.txt | 3 years ago | |
README.md
sitc
Exercises for Intelligent Systems Course at Universidad Politécnica de Madrid, Telecommunication Engineering School. This material is used in the subjects
- SITC (Sistemas Inteligentes y Tecnologías del Conocimiento) - Master Universitario de Ingeniería de Telecomunicación (MUIT)
- TIAD (Tecnologías Inteligentes de Análisis de Datos) - Master Universitario en Ingeniera de Redes y Servicios Telemáticos)
For following this course:
- Follow the instructions to install the environment: https://github.com/gsi-upm/sitc/blob/master/python/1_1_Notebooks.ipynb (Just install 'conda')
- Download the course: use 'https://github.com/gsi-upm/sitc' (or clone the repository to receive updates).
- Run in a terminal in the folder sitc: jupyter notebook (and enjoy)
Topics
- Python: quick introduction to Python
- ML-1: introduction to machine learning with scikit-learn
- ML-2: introduction to machine learning with pandas and scikit-learn
- ML-3: introduction to machine learning. Neural Computing
- ML-4: introduction to Evolutionary Computing
- ML-5: introduction to Reinforcement Learning
- NLP: introduction to NLP
- LOD: Linked Open Data, exercises and example code