This project uses XGBoost for intrusion detection in cloud computing, achieving 99.17% accuracy on the KDDcup99 dataset. Leveraging AWS services like Amazon S3 and SageMaker, we ensure robust security and efficiency in handling large datasets.

This project focuses on building end-to-end machine learning pipeline using AWS SageMaker to predict the price range of mobile phones based on their specifications, enhancing consumer decision-making and streamlining the development process.

Solution for Kaggle competition "Bike Sharing Demand". The solution using AutoGluon's Tabular Predictor provides a good overview of which model to choose as the base model for this problem.

This repository serves as a learning hub for AWS, covering key services like S3 buckets, EC2 instances, and SageMaker. Explore how to leverage these tools for storage, computing, and machine learning tasks.

This website focuses on the data visualization of football data, encompassing actual match results, generated predictions by AWS SageMaker, and sentiment analysis based on news data for five football teams

All the available resources to master MLOPS from scratch

ACK service controller for Amazon SageMaker

This repository is dedicated to small projects and some theoretical material that I used to get into NLP and LLM in a practical and efficient way.

Sentiment Analysis on AWS

Proyecto donde automatizamos el proceso de recolección , exploración, optimización y visualización de datos, como así también el entrenamiento de modelos de Machine Learning utilizando Amazon Web Services (AWS)

Streamlit EDA Dashboard Powered by AWS Cloud

This repository hosts a proof-of-concept (POC) project aimed at developing a domain expert model tailored for the Information Technology (IT) domain. The project employs advanced NLP techniques to train and deploy in AWS SageMaker a large language model, capable of generating informative and contextually relevant text responses in the IT domain.

MLOps End-to-End Example using Amazon SageMaker Pipeline, AWS CodePipeline and AWS CDK

A simple jupyter notebook that will help you fine tune your own Instruct Pix2Pix Stable Diffusion model.

AWS SageMaker, SeldonCore, KServe, Kubeflow & MLflow, VectorDB

Implement CI/CD pipelines to train and deploy machine learning models using Github Actions

Final Project for AWS AI and ML Scholarship Advance Cohort

Advanced Machine Learning Regression: Predicting Car Prices

Deploying a Huggingface model to AWS SageMaker with Snowflake connector.