mlflow

Project to automate training of Classification model using custom scripts and MLFlow. Classification model is trained using XGBoost library.

A CBIR and classification system that uses both representation learning and handcrafted features to build the image descriptors.

Simulation of a real hospital scenario with a ML model in production

Train YOLOv5 for breed classification on Oxford Pets III dataset from scratch on Google Colab, and serve through Dockerized implementation of a flask-based HTML/JS frontend and an asynchronous API service on FastAPI. Use of MLFlow for logging.

this project it to practice all concepts and knowledge in the course mlops-zoomcamp