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ML Training Pipeline

End-to-end machine learning pipeline for model training and deployment.

PythonPyTorchDockerAWS
GitHub

Overview

This project demonstrates a production-ready ML pipeline that automates the full lifecycle of machine learning models.

Key Features

  • Data Pipeline: Automated data ingestion, cleaning, and feature engineering
  • Training: Distributed training with PyTorch
  • Evaluation: Comprehensive metrics and model comparison
  • Deployment: Containerized deployment with Docker

Results

  • Reduced model iteration time by 60%
  • Achieved 95% reproducibility across training runs