https://github.com/arturobp3/machine_learning

Projects that has been developed in the Machine Learning and Big Data subject. Python is the programming language used in them.
https://github.com/arturobp3/machine_learning

linear-regression neural-network numpy pandas python scikit-learn support-vector-machines

Last synced: 16 days ago
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Projects that has been developed in the Machine Learning and Big Data subject. Python is the programming language used in them.

• Host: GitHub
• URL: https://github.com/arturobp3/machine_learning
• Owner: arturobp3
• Created: 2018-11-11T20:20:00.000Z (about 6 years ago)
• Default Branch: master
• Last Pushed: 2019-09-27T19:01:33.000Z (over 5 years ago)
• Last Synced: 2024-11-17T08:19:02.347Z (3 months ago)
• Topics: linear-regression, neural-network, numpy, pandas, python, scikit-learn, support-vector-machines
• Language: Jupyter Notebook
• Homepage:
• Size: 30.7 MB
• Stars: 2
• Watchers: 1
• Forks: 1
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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Projects that has been developed in the Machine Learning and Big Data university subject. Python is the programming language used in them.


# Proyecto Final

Analysis performed on a dataset that contains data about clients that have requested a bank credit. Classification models have been used to determine if the client will receive the credit or not, based on the characteristics of each one. The data of each person has been replaced by symbols to protect their confidentiality.

* [Análisis en PDF](https://github.com/arturobp3/Machine_Learning/blob/master/Proyecto/Credit%20Approval.pdf)

* [Código realizado en Jupyter](https://github.com/arturobp3/Machine_Learning/blob/master/Proyecto/Credit%20Approval.ipynb)

# Prácticas Realizadas

## Práctica 0: Python

* [Enunciado](https://github.com/arturobp3/Machine_Learning/blob/master/docs/practica0/p0.pdf)

## Práctica 1: Regresión Lineal

* [Enunciado](https://github.com/arturobp3/Machine_Learning/blob/master/docs/practica1/p1.pdf)

* [Archivos necesarios](https://github.com/arturobp3/Machine_Learning/blob/master/docs/practica1/p1.zip)

## Práctica 2: Regresión Logística (Clasificación)

* [Enunciado](https://github.com/arturobp3/Machine_Learning/blob/master/docs/practica2/p2.pdf)

* [Archivos necesarios](https://github.com/arturobp3/Machine_Learning/blob/master/docs/practica2/p2.zip)

## Práctica 3: Regresión Logística multi-clase y Redes Neuronales

* [Enunciado](https://github.com/arturobp3/Machine_Learning/blob/master/docs/practica3/p3.pdf)

* [Archivos necesarios](https://github.com/arturobp3/Machine_Learning/blob/master/docs/practica3/p3.zip)

## Práctica 4: Entrenamiento de Redes Neuronales

* [Enunciado](https://github.com/arturobp3/Machine_Learning/blob/master/docs/practica4/p4.pdf)

* [Archivos necesarios](https://github.com/arturobp3/Machine_Learning/blob/master/docs/practica4/p4.zip)

## Práctica 5: Regresión lineal regularizada: Sesgo y Varianza

* [Enunciado](https://github.com/arturobp3/Machine_Learning/blob/master/docs/practica5/p5.pdf)

* [Archivos necesarios](https://github.com/arturobp3/Machine_Learning/blob/master/docs/practica5/ex5data1.mat)

## Práctica 6: Support Vector Machines

* [Enunciado](https://github.com/arturobp3/Machine_Learning/blob/master/docs/practica6/p6.pdf)

* [Archivos necesarios](https://github.com/arturobp3/Machine_Learning/blob/master/docs/practica6/p6.zip)