AutoML Studio

## Project Objective

Build a complete AutoML platform capable of training, comparing and deploying machine learning models with minimal manual intervention.

The project focuses on Machine Learning Engineering practices rather than building only another prediction dashboard.

## Planned Modules

• ✓Automatic dataset profiling
• ✓Feature preprocessing pipeline
• ✓Regression & Classification detection
• ✓Model comparison dashboard
• ✓Hyperparameter optimization using Optuna
• ✓Model explainability using SHAP
• ✓Experiment tracking using MLflow
• ✓Model registry
• ✓One-click deployment

## Architecture

• ✓Dataset Upload
• ✓Automatic Data Validation
• ✓Feature Engineering
• ✓Model Training
• ✓Evaluation
• ✓Explainability
• ✓Deployment

## Learning Goals

• ✓MLOps fundamentals
• ✓Experiment tracking
• ✓Model versioning
• ✓Pipeline engineering
• ✓Production deployment
• ✓Scalable ML systems

## Tech Stack

## Completion Date

Upcoming