/masters_degree_projects

Primary LanguageJupyter Notebook

Master's Degree Projects

Contributors Stars

Description

The purpose of this repo is to bring together the main data science projects done during the Master's Degree in Data Science of the Universidad Autónoma de Madrid. You can find the Master's Degree web here.

In such way, the different projects are classified by the name of the subject. Also, as most of them are developed in a Jupyter Notebook, you can have a quick view of the technologies used checking out the following table:

Data Science Projects

Nº Name of the subject Project Technology Authors
1 Theory of Information Calculation of mutual information between neural time series Python Ignacio Córdova Pou & Daniel Beteta Francisco
2 Advanced Methods in Statistics Parametric estimation exercises R Daniel Beteta Francisco
3 Advanced Methods in Statistics Non parametric estimation exercises R Daniel Beteta Francisco
4 Advanced Methods in Statistics Regression exercises R Daniel Beteta Francisco
5 Advanced Methods in Statistics Supervised learning exercises R Daniel Beteta Francisco
6 Advanced Methods in Machine Learning Support vector machines task Python Mercedes García Villaescusa & Daniel Beteta Francisco
7 Advanced Methods in Machine Learning Kernel principal components analysis task Python Mercedes García Villaescusa & Daniel Beteta Francisco
8 Advanced Methods in Machine Learning Variable elimination and gradient boosting task Python Mercedes García Villaescusa & Daniel Beteta Francisco
9 Stochastic Processes Stochastic processes in discrete time Python Daniel Beteta Francisco
10 Stochastic Processes Stochastic processes in continuous time Python Ignacio Córdova Pou, Luís Sánchez Polo & Daniel Beteta Francisco
11 Stochastic Processes Stochastic and ordinary differential equations Python Ignacio Córdova Pou, Luís Sánchez Polo & Daniel Beteta Francisco
12 Large Scale Data Processing Introduction to pyspark PySpark Pablo López Perez & Daniel Beteta Francisco
13 Large Scale Data Processing Football analysis with pyspark PySpark Pablo López Perez & Daniel Beteta Francisco
14 Large Scale Data Processing Introduction to cuda computing CUDA Pablo López Perez & Daniel Beteta Francisco
15 Large Scale Data Processing Introduction to quantum computing Python Pablo López Perez & Daniel Beteta Francisco
16 Data Management Graphical data exploration R Pablo López Perez & Daniel Beteta Francisco
17 Data Management Anonymization task Python Pablo López Perez & Daniel Beteta Francisco
18 Data Management Movie data analysis Python Pablo López Perez & Daniel Beteta Francisco
19 Numerical Computation Errors and approximations of functions Python Blanca Cano Camarero, Iker Villegas Labairu & Daniel Beteta Francisco
20 Numerical Computation Application of monte carlo methods to bayesian computing Python Javier Irigoyen Muñoz, Santiago Monteso Fernández & Daniel Beteta Francisco
21 Deep Learning for Image Processing Image Classification with PyTorch Simple CNN PyTorch Daniel Beteta Francisco
22 Deep Learning for Image Processing Image Classification with PyTorch AlexNet PyTorch Daniel Beteta Francisco
23 Deep Learning for Image Processing Image Classification with PyTorch Transfer learning PyTorch Daniel Beteta Francisco
24 Deep Learning for Biometric Information Processing Facial Recognition Task Python Daniel Beteta Francisco
25 Reinforcement Learning GridWorld with SARSA and Q-learning Python Ignacio Córdova Pou, Bruno Muñoz Marcos & Daniel Beteta Francisco
26 Reinforcement Learning Contextual and Non-contextual Multiarmed Bandits Python Ignacio Córdova Pou, Bruno Muñoz Marcos & Daniel Beteta Francisco