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README.md
sitc
Exercises for Intelligent Systems Course at Universidad Politécnica de Madrid, Telecommunication Engineering School. This material is used in the subjects
- CDAW (Ciencia de datos y aprendizaje en automático en la web de datos) - Master Universitario de Ingeniería de Telecomunicación (MUIT)
- ABID (Analítica de Big Data) - 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: a 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-21: preprocessing and visualizatoin
- 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
- SNA: Social Network Analysis