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Project with examples of different recommender systems created with the Surprise framework. Different algorithms (with a collaborative filtering approach) are explored, such as KNN or SVD.

Home Page: https://ansegura7.github.io/RS_Surprise/

License: MIT License

Jupyter Notebook 42.91% HTML 57.09%
knn model-tuning python recommender-system surprise svd

rs_surprise's Introduction

Hi there 👋

My name is Andrés Segura-Tinoco. I was born in Colombia and grew up in Venezuela.
Currently, I am a third-year Computer Science PhD student at Universidad Autónoma de Madrid.

I work actively in the ArgRecSys team of the Information Retrieval Group (IRG) at UAM.

📚 My research interests are in the fields of:

  • Explainable Artificial Intelligence (XAI)
  • (Argument-based) Recommender Systems
  • Machine Learning and Deep Learning
  • NLP and Argument Mining

You can find more information about my research in my Google Scholar profile.

💻 and my favorite programming languages are:

  • Python 🐍
  • Java
  • [C#, VB].NET
  • JavaScript
  • R
  • SQL

📧 Feel free to contact me on Twitter (@SeguraAndres7) or LinkedIn.

E-Mail ansegura7

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