Practicas del Grado en Inteligencia Artificial y Machine Learning: R, TimeSeries, SVM, NLP, Decision Trees
Machine Learning grade practices using R, TimeSeries, SVM, NLP, Decision Trees.
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- Practicas del Grado en Inteligencia Artificial y Machine Learning: R, TimeSeries, SVM, NLP, Decision Trees
- Machine Learning grade practices using R, TimeSeries, SVM, NLP, Decision Trees.
Email: sergio.alegre.arribas EN gmail.com
LinkedIn: https://www.linkedin.com/in/sergioalegre
Website: http://me.sergioalegre.es
- R
- Machine Learning
- Time Series
- Decission Trees
- Support Vector Machine aka SVM
- Procesamiento del lenguaje natural / Natural languaje processing aka NLP
- Ejemplos sencillos de diversas técnicas de aprendizaje de diferentes datasets populares.
- Simple example of diffentent ML techniques using popular datasets.
- Anaconda para R Studio o cuenta en Colab o servicio similar.
- Anaconda for R Studio o have a Colab account or similar service.
- Solamente instalar Anaconda e instalar las librerias si alguna faltara.
- Just install Anaconda and install, if needed, any missing dependency (library).
- Simplemente importa el archivo .R
- Just import .R file.
- En este repo iré almacenando más ejemplos comentados.
- I'll add more examples.
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.
- Fork the Project
- Create your Feature Branch (
git checkout -b feature/AmazingFeature) - Commit your Changes (
git commit -m 'Add some AmazingFeature') - Push to the Branch (
git push origin feature/AmazingFeature) - Open a Pull Request
Distributed under the MIT License. See LICENSE for more information.