title	AutoStack Engine
emoji	🚀
colorFrom	blue
colorTo	purple
sdk	docker
app_port	8000
pinned	false

AutoStack AI — The Autonomous ML Lifecycle Platform

Production-grade ML workflow from Raw CSV to Low-Latency REST API in under 60 seconds.

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⚡ The Vision

AutoStack is not just another AutoML tool. It is a Production-First ML Engine designed for teams who need to scale intelligence without the operational mess. It automates the most brittle parts of the machine learning lifecycle—feature engineering, hyperparameter tuning, drift detection, and production-ready inference—within a sleek, glassmorphic dashboard.

🌐 Live Platform Demo →

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🚀 Key Capabilities

🧠 Autonomous Pipeline Synthesis

The engine profiles your data in real-time, handling missing values through probabilistic imputation and selecting optimal encoding strategies (Target vs. One-Hot) based on cardinality.

⚡ Neural Ensemble Engine

Runs parallel hyperparameter optimization on a curated stack of Gradient Boosted Trees and Stacking Regressors. Verified to deliver high-accuracy models in resource-constrained environments.

🔍 Integrated Explainability (SHAP)

Every prediction is accompanied by structural explanations. Understand why the model made a decision with built-in SHAP visualizations available directly in the production API.

📡 Instant Production API

One-click deployment to a low-latency REST endpoint. Engineered for high-frequency environments with sub-10ms inference and built-in statistical drift monitoring.

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🛠 Tech Stack

• Frontend: Next.js 16 (Turbopack), Tailwind CSS, Framer Motion, Lottie-React.
• Backend Core: FastAPI (Python 3.9), Scikit-Learn, LightGBM, Pandas.
• Database/Auth: Supabase (PostgreSQL).
• Inference Cloud: Hugging Face Spaces (Dockerized Engine).
• Observability: Vercel Analytics, Recharts.

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📐 Architecture

graph TD
    User([End User]) -->|Upload CSV| Dashboard[Next.js Studio]
    Dashboard -->|POST /train| Engine[Hugging Face Engine]
    Engine -->|Profile| Profiler[Data Profiler]
    Profiler -->|Search| Tuner[Optuna Hyper-Tuner]
    Tuner -->|Serialize| ModelStore[Joblib Pipeline]
    Engine -->|Return| Results[Dashboard Metrics]
    
    API[Live REST API] -->|POST /predict| ModelStore
    ModelStore -->|Return| Preds[Predictions + SHAP]
    Preds -->|Alert| Drift[Drift Monitor]

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🚦 Getting Started

🐍 Local Engine Setup

# Clone the repository
git clone https://github.com/VedantJadhav701/Autonomous_ML_Builder.git

# Install backend dependencies
cd backend
pip install -r requirements.txt

# Launch the FastAPI Engine
uvicorn app.main:app --host 0.0.0.0 --port 8000

⚛️ Frontend Dashboard Setup

cd frontend
npm install
npm run dev

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📈 Enterprise & Bespoke Solutions

For organizations requiring:

• Unlimited Data Processing (Millions of rows)
• Deep Neural Network Architectures (PyTorch/GPU)
• Custom Database Connectors (Snowflake, BigQuery)
• Air-Gapped Private Cloud Deployment

📅 Book a Strategy Session →

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📜 License & Author

Distributed under the MIT License. Built with 💎 and coffee by Vedant Jadhav.

• LinkedIn: linkedin.com/in/vedantjadhav-ai
• Portfolio: autostack-ai.vercel.app