Skip to content
View aghents's full-sized avatar
🏠
Working from home
🏠
Working from home
15 followers · 82 following

Achievements

Achievement: YOLOAchievement: Pull Shark

Achievements

Achievement: YOLOAchievement: Pull Shark

Highlights

  • Pro

Organizations

@Trabajos-LyP

Block or report aghents

Block user

Prevent this user from interacting with your repositories and sending you notifications. Learn more about blocking users.

You must be logged in to block users.

Please don't include any personal information such as legal names or email addresses. Maximum 100 characters, markdown supported. This note will be visible to only you.
Report abuse

Contact GitHub support about this user’s behavior. Learn more about reporting abuse.

Report abuse
aghents/README.md

Hey there, I'm Agustin! 👋

I'm an engineering student from Valparaíso, Chile, with a passion for Machine Learning, and I’m excited to begin my Master's degree in this field.
const Agustin = {
code: [Python, R, C, Javascript, C++],
tools: [React, Vue.js, Django, Flask, Jupyter, LaTex, SQL, GIT, Docker, tensorflow],
learning_rn: [Pytorch, Deeplearning Aplications, Langchain, CI-CD tools]
}

About myself

  • 🌱 I’m currently learning NLP aplications
  • 👯 I’m currently looking to collaborate on Machine learning projects.
  • 📫 How to reach me: [email protected] | agustinghent[at]gmail[dot]com
  • ⚡ Fun facts:
    • I'm very proficient in Spanish (I'm chilean, buena culiao!), speak proper English and some Portuguese.
    • On my free time I enjoy training crossfit and playing the guitar.
    • I've never broken a bone.

Pinned Loading

  1. my-classnotes my-classnotes Public

    Just a repo with all my classnotes from college and my personal studies. visit https://agustinesoto.github.io/my-classnotes/

  2. Open-Source-UAI/cluster-hpc Open-Source-UAI/cluster-hpc Public

    Guides, tutorials and documentation about the central HPC Cluster of Universidad Adolfo Ibáñez

    1

  3. EasyHPC EasyHPC Public

    Forked from pescap/EasyHPC

    Documentation on Physics-Informed Neural Networks and their implementation