mirror of https://github.com/gsi-upm/sitc synced 2024-09-19 20:01:43 +00:00

Go to file

Carlos A. Iglesias ed596c2ef3 Updated README		2018-05-03 11:27:07 +02:00
lod	Fix SPARQL regex exercise	2018-03-20 16:46:52 +01:00
ml1	Fix typo in axis	2018-02-27 16:14:18 +01:00
ml2	spiral rearranged	2018-04-26 17:19:56 +02:00
ml3	h parameter can be changed	2018-04-26 18:05:34 +02:00
ml4	Added ml4	2018-04-26 12:50:14 +02:00
ml5	Added ml5 r- Reinforcement Learning	2018-05-03 11:24:58 +02:00
nlp	Added rd grammar	2017-04-20 17:27:44 +02:00
python	Corregida errata asignación funciones	2018-02-15 19:01:30 +01:00
.gitignore	Added gitignore	2016-03-28 12:34:10 +02:00
logo.jpg	Add SPARQL notebooks	2018-03-13 13:32:29 +01:00
README.md	Updated README	2018-05-03 11:27:07 +02:00

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'
Run in a terminal in the foloder 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