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Heber Trujillo's Projects

character-level-lstm icon character-level-lstm

A general framework to implement LSTM on text corpus to generate sequences of characters.

cronos icon cronos

Cronos is a machine learning logistic system to optimize stock allocation to a customer’s orders.

curso-python-cac icon curso-python-cac

Material del curso de programación en Python del Colegio de Actuarios de Cataluña

customer-churn-prod icon customer-churn-prod

This project implements an ML model to identify credit card customers that are most likely to churn. However, the main focus will be following coding (PEP8) and engineering best practices for implementing software (modular, documented, and tested).

deepspeech icon deepspeech

A TensorFlow implementation of Baidu's DeepSpeech architecture

deploy-ml-model-fastapi-heroku icon deploy-ml-model-fastapi-heroku

This repo shows how to deploy a simple machine learning classification model following CI/CD principles with FastAPI on Heroku.

docker-python icon docker-python

This repo demonstrate how to use Docker to deploy a simples flask app

docs icon docs

TensorFlow documentation

fashion-mnist icon fashion-mnist

A MNIST-like fashion product database. Benchmark :point_right:

fb.resnet.torch icon fb.resnet.torch

Torch implementation of ResNet from http://arxiv.org/abs/1512.03385 and training scripts

flask-jwt icon flask-jwt

JWT (JSON Web Tokens) for Flask applications

flaskwebsocialblog icon flaskwebsocialblog

A Social Blog web page project to showcase how to use Flask, SQLalchemy and Bootstrap

fraud-detection-system icon fraud-detection-system

This repository contains a robust Machine Learning-based Fraud Detection System designed to identify and flag potentially fraudulent transactions in near real-time.

lego-robotics icon lego-robotics

This repo contains python code to operate various lego projects.

machine-learning-devops icon machine-learning-devops

Software engineering fundamentals needed to successfully streamline the deployment of data and machine-learning models in a production-level environment.

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