AI Makerspace: Blueprints for developing machine learning applications with state-of-the-art technologies.

Example project with a complete MLOps cycle: versioning data, generating reports on pull requests and deploying the model on releases with DVC and CML using Github Actions and IBM Watson. Part of the Engineering Final Project @ Insper

Implementation of USAD (UnSupervised Anomaly Detection on multivariate time series) in PyTorch Lightning

This project contains the production ready Machine Learning(Deep Learning) solution for detecting and classifying the brain tumor in medical images

AIOps-project-DVC-NLP-usecase

This project contains the production ready Machine Learning solution to make the prediction on the batch of data coming from Air Pressure system (APS) sensors

An example project, showcasing a DVC pipeline using SageMaker SDK for data preparation and model training

This project contains the production-ready Machine Learning solution for detecting and classifying Covid-19, Viral disease, and No disease in posteroanterior and anteroposterior views of chest x-ray

Census data classification model with Random Forest Classifier

Skeleton for DVC pipeline to evaluate multiple models together

THIS WEB_APP ALLOWS USER TO PREDICT THE AIR QUALITY INDEX BASED ON FEATURES LIKE TEMPERATURE, WIND VELOCITY, ATMOSPHERIC PRESSURE

This project aims to classify chicken fecal samples into two categories: diseased (Coccidiosis) and healthy. The classification is based on analyzing images of the fecal samples using computer vision techniques.

This repository offers a comprehensive solution for chest disease detection, covering data ingestion, preprocessing, model training, and CI/CD deployment pipelines. From raw data to automated deployment, streamline your chest disease detection process with our end-to-end solution.

An example of DVC pipeline with a Docker-wrapped command

Small collection of dvc tutorials

GAN based Super resolution media engine

A boilerplate template for DVC(Data Version Control) Project

This project explains how to automate data and machine learning pipelines using various tools, such as DVC, OmegaConf, Hydra, and MLFlow to achieve that.

This contains the dvc files created from data versioning.