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# 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)
- CDAW (Ciencia de datos y aprendizaje en automático en la web de datos) - Máster Universitario de Ingeniería de Telecomunicación (MUIT)
- ABID (Analítica de Big Data) - Máster Universitario en Ingeniería 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')
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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
* ML-1: Introduction to machine learning with scikit-learn
* ML-2: Introduction to machine learning with pandas and scikit-learn
* ML-21: Preprocessing and visualization
* 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