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Repositorio para las prácticas de las asignaturas del máster de ciencia de datos en la UAM.

License: MIT License

Shell 0.54% Python 19.59% R 0.56% MATLAB 17.72% TeX 61.25% Makefile 0.33%

mcd01's Introduction

Master's degree in Data Science (UAM)

Exercises, assignments and exams completed in the academic year 2021/22. Mostly made with my good friend @Ocete.

Detailed descriptions of the assignments done in each of the subjects can be found in each subject's folder.

1st term

CN: Computación Numérica. (Numerical computation)

GD: Gestión de Datos. (Big data storage)

MAE: Métodos Avanzados en Estadística. (Advanced methods in statistics)

MAAA: Métodos Avanzados en Aprendizaje Automático. (Advanced methods in machine learning)

PDGE: Procesamiento de Datos a Gran Escala. (Big data techniques)

PE: Procesos Estocásticos. (Stochastic processes)

PST: Procesamiento de Señal y Transformadas. (Signal processing and Fourier transform)

TI: Teoría de la Información. (Information theory)

2nd term

OPT: Optimización (Optimization)

MF: Métodos Funcionales. (Functional methods in machine learning)

BIO: Aprendizaje profundo para señales biométricas. (Deep learning for biometric signals)

PIT: Procesamiento de información temporal. (Temporal information processing)

NLP: Procesamiento de lenguaje natural. (Natural language processing)

AUDIO: Aprendizaje profundo para señales de audio. (Deep learning for audio signals)

BAYES: Métodos bayesianos en aprendizaje automático. (Bayesian methods in machine learning)

VIDEO: Aprendizaje profundo para imágenes y video. (Deep learning for image and video)

mcd01's People

Contributors

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