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