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Always Coding
:octocat:
Always Coding
93 followers · 27 following

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Achievements

Achievement: Starstruckx2Achievement: QuickdrawAchievement: YOLOAchievement: Pull Sharkx3Achievement: Arctic Code Vault Contributor

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@argrecsys

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ansegura7/README.md

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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  1. Algorithms Algorithms Public

    Free hands-on course with the implementation (in Python) and description of several computational, mathematical and statistical algorithms.

    HTML 132 23

  2. NLP NLP Public

    Free hands-on course with the implementation (in Python) and description of several Natural Language Processing (NLP) algorithms and techniques, on several modern platforms and libraries.

    HTML 79 15

  3. MachineLearning MachineLearning Public

    Practical course, which starting from Data Science offers examples (with Python code) and explanation (in Twitter threads) on concepts and techniques of Machine Learning, Deep Learning and NLP.

    Jupyter Notebook 76 13

  4. TwitterAnalytics TwitterAnalytics Public

    Web Mining project in which Descriptive Statistics and NLP techniques are used to analyze the behavior of a Twitter account and the content of their respective tweets.

    HTML 9 4

  5. RS_Surprise RS_Surprise Public

    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.

    HTML 9 1

  6. RS_CF_LastFm RS_CF_LastFm Public

    Recommender systems with collaborative filtering created with Apache Mahout framework. The system uses a Music Recommendation dataset for research purposes as input, but you can train it and predic…

    Java 5 3