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anfis_energyefficience

auto-mail-newsletter

badgr-lite

Automate awarding Open Badges to recipients without the overhead of a server

bash_tutorial

Exercises for learning the bash command line.

bectome

checktemplate

cnn_caltech101silhouettes

cnn_museum_classifier

deeplearningai-maths_for_ds_ml

evolution_strategies-vessel_design_optimization

extension-pt-nov22

fisevi-web_scrapping

github-readme-stats

:zap: Dynamically generated stats for your github readmes

hpc_dl_training

Project developed and ran in cluster from Barcelona Supercomputing Center (BSC)

hundirlaflota-oop

hundirlaflota_pytest

En este proyecto desarrollaremos un Hundir La Flota todos juntos.

iml-lab2-visualization

introduction-to-quantum-computing-qiskit

Notes and examples from the course Introduction to Quantum Computing (https://qiskit.org/learn/course/introduction-course/)

kaggle-with-aws

Train DL Models from Kaggle in CPU (local) VS GPU (AWS EC2)

miniproject-subsequence_detector

nlp-mision-mandalorian

Project in Spanish [future releases may be in English]. This is a personal NLP project for self-development and amusement inspired in the popular Disney serie "Star Wars: The Mandalorian". A transmission classification subsystem is built as part of the Communications Interception System.

nlp_semantictextualsimilarity

SemEval 12's Semantic Textual Similarity task, specifically in paraphrase detection

sevici-app

sql_workshop

Workshop SQL impartido para los alumnos de los Bootcamps de Data Science y Full Stack de The Bridge

svl_ds_febrero23

telco-churn-ml

Churn is a one of the biggest problem in the telecom industry. Research has shown that the average monthly churn rate among the top 4 wireless carriers in the US is 1.9% - 2%.

udacity_azure-ml-capstone

This project aims to use the knowledge obtained from Udacity Machine Learning Engineer wit Azure Nanodegree to solve an interesting problem. In this project, two ML models are created: one using AutoML and one customized model whose hyperparameters are tuned using HyperDrive. Performance of both the models are compared and the best performing model is going to be deployed. This project will demonstrate author's ability to use an external dataset in workspace, train a model using the different tools available in the AzureML framework as well as the ability to deploy the model as a web service.

udacity_azure-ml-ops

Udacity Machine Learning Engineer Nanodegree Project. Both the Azure ML Studio and the Python SDK will be used in this project. First we start with authentication and then run an Automated ML experiment to deploy the best model. Next, we will enable Application Insight to review important information about the service when consuming the model. And finally, we will create, publish, and interact with a pipeline. Once all of that is complete, we will create a short screencast and a README to demonstrate all your hard work.

udacity_azure-ml-pipeline

In this project, the goal is to create and optimize an ML pipeline. For that aim, it is used a custom-coded model—a standard Scikit-learn Logistic Regression—whose hyperparameters are optimized using HyperDrive. In addition to this, AutoML is used to build and optimize a model on the same dataset, so that it is possible to compare the results of the two methods.

wordle-game

Wordle es un juego de palabras basado en la web, creado y desarrollado por el ingeniero de software galés Josh Wardle, y publicado por The New York Times Company desde 2022. Los jugadores tienen seis intentos de adivinar una palabra de cinco letras, y cada vez que adivinan una palabra reciben una respuesta en forma de fichas de colores que indican si las letras coinciden u ocupan la posición correcta. La mecánica es casi idéntica a la del juego de papel y lápiz Jotto, de 1955, y a la de la franquicia de juegos televisivos Lingo. Wordle tiene una única solución diaria, en la que todos los jugadores intentan adivinar la misma palabra.