In this project I played with mlflow, streamlit and fastapi to create a training and prediction app on digits

MLOps learning using SageMaker and MNIST

Deep learning on mnist dataset. MLOps project from course 02476 DTU

Project to apply my MLOps architecture to the MNIST deep learning model.

A complete MLOps pipeline for MNIST digit classification using TensorFlow, DVC, MLflow, Docker, and FastAPI — trained, versioned, and deployed to the cloud as part of an end-to-end learning project.

End-to-end machine learning project for handwritten digit recognition using the MNIST dataset. Includes model training, evaluation, and experiment tracking with MLflow, demonstrating scalable MLOps practices and deployment-ready model management.

Develop a Machine Learning (ML) model - MLOps pipeline for one of the use case - Sentiment Analysis on Movie Reviews - IMDB dataset, Handwritten Digit Recognition - MNIST dataset, Email Spam Detection - email spam sataset.