MNIST MLOps Project

Project Overview

This project implements an end-to-end machine learning pipeline for handwritten digit classification using the MNIST dataset. The pipeline includes model training with PyTorch, monitoring with Weights and Biases (W&B), deployment with FastAPI, and containerization using Docker.

Technologies Used

• PyTorch
• FastAPI
• Weights and Biases (W&B)
• Docker

Instructions for Running the Code Locally

Prerequisites

Ensure you have the following installed:

• Python 3.9 or higher
• Pip (Python package manager)
• Virtual Environment (optional, but recommended)

Clone the Repository

git clone https://github.com/jamesafful/mnist-mlops.git
cd mnist-mlops