sergioalegre / Pandas-matplotlib-Sklearn-Scipy-Tensorflow-Keras

Practicas del Grado en Inteligencia Artificial y Machine Learning 2019-2020

Python with Pandas-matplotlib-Sklearn-Scipy-Tensorflow-Keras

Practicas del Grado en Inteligencia Artificial y Machine Learning 2019-2020
IA & Machine Learning grade practices 2019-2020
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About The Project

• Practicas del Grado en Inteligencia Artificial y Machine Learning 2019-2020
  
  
• IA & Machine Learning grade practices 2019-2020
  
  

Contact

Email: sergio.alegre.arribas EN gmail.com
LinkedIn: https://www.linkedin.com/in/sergioalegre
Website: http://me.sergioalegre.es

Built With

• Python
• Machine Learning
• Pandas
• matplotlib
• sklearn
• scipy
• Tensorflow
• Keras

Datasets: MNIST, IRIS, Fashion, Enfermedades corazon / heart diseases

Getting Started

• Ejemplos sencillos de diversas técnicas de aprendizaje de diferentes datasets populares. Ejemplos de Regresión lineal, Random forest, SVM, Clustering con K-Means y Tensorflow.
  
  
• Simple example of diffentent ML techniques using popular datasets. Examples based Linear Regression, Random Forest, Support Vector Machine, K-Means Clustering and Tensorflow.

Prerequisites

• Anaconda para ejecurtar los Juniper notebooks / R Studio o cuenta en Colab o servicio similar.
  
  
• Anaconda to run Juniper notebooks / R Studio o have a Colab account or similar service.

Installation

• Solamente instalar Anaconda e instalar las librerias si alguna faltara.
  
  
• Just install Anaconda and install, if needed, any missing dependency (library).

Usage

• Simplemente importa el Juniper notebook o el archivo .R
  
  
• Just import notebook or .R file.

Roadmap

• En este repo iré almacenando más ejemplos comentados.
  
  
• I'll add more examples.

Contributing

Contributions are what make the open source community such an amazing place to be learn, inspire, and create. Any contributions you make are greatly appreciated.

1. Fork the Project
2. Create your Feature Branch (git checkout -b feature/AmazingFeature)
3. Commit your Changes (git commit -m 'Add some AmazingFeature')
4. Push to the Branch (git push origin feature/AmazingFeature)
5. Open a Pull Request

License

Distributed under the MIT License. See LICENSE for more information.

Contact

Email: sergio.alegre.arribas EN gmail.com
LinkedIn: https://www.linkedin.com/in/sergioalegre