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Hi 👋, I'm Santiago Ahumada Lozano

A Mathematics, Machine Learning and Data Science Student!

coding

santiagoahl

santiagoahl

sahumadaloz

  • 🔭 I’m currently working on RNA taxonomy prediction

  • 🌱 I’m currently learning AWS, FastAPI, TensorFlow

  • 👯 I’m looking to collaborate on Deep Learning research

  • 🤝 I’m looking for help with more machine learning enthusiasts

  • 📝 I regularly write articles on https://elparaisodecantor.wordpress.com/sahumadal/

  • 💬 Ask me about Scikitlearn, Tensorflow, Pytorch

  • 📫 How to reach me [email protected]

  • 📄 Know about my experiences I'm a road cycling passionate 🚵🏻‍♂️

  • ⚡ Fun fact Agua panela are my breakfast, lunch and dinner when working @ home!

Connect with me:

sahumadaloz santiago-ahumada-lozano 19552094 santiagoahumadal

Languages and Tools:

gcp aws kubernetes linux mysql pandas python pytorch scikit_learn tensorflow

santiagoahl

 santiagoahl

santiagoahl

Santiago Ahumada L's Projects

clustering-algorithms icon clustering-algorithms

In this repository I am gonna show the main and most popular non-supervised clustering algorithms with short explanations.

digit-recognition icon digit-recognition

In this repository I'm going to implement a machine learning clustering algorithm in order to recognize handwritten digits

dogs-vs-cats icon dogs-vs-cats

Dogs Vs Cats is a CNN based model. Its purpose is to classify a images dataset into two classes: Cats and Dogs.

fda-recognizer icon fda-recognizer

Here you can put your own alphabet and the transition diagram, then, the automata will recognize only the accepted strings.

my-own-interpreter icon my-own-interpreter

¡Hello there! In this repository I am supposed to show the main components of my own programming language (LLP). Its lexer within a parser,(which generates abstract syntax trees), but also an inner object representation and a REPL evaluator.

platzi-beans-classification icon platzi-beans-classification

A computer vision model using a pre-trained model from the hugging face hub. It classifies beans' photos by its quality.

platzi-customer-segmentation icon platzi-customer-segmentation

Unsupervised learning algorithms built to make costumer segmentation. Clustering is implemented with DBSCAN. We made data preprocessing with PCA.

platzi-dry-beans-classification icon platzi-dry-beans-classification

Here we built a multinomial logistic regression classifier with scikit-learn. It takes numerical data of a bean an predicts which class does it belong to.

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