Welcome to HAutoML
HAutoML is an open-source Automated Machine Learning (AutoML) platform developed by OptiVisionLab, School of Information and Communications Technology, Hanoi University of Industry.
The platform automates the entire machine learning workflow — from data preprocessing, model selection, hyperparameter tuning, to model deployment — enabling users to easily build high-accuracy models without requiring in-depth expertise in programming or data science.
🎯 HAutoML Vision
HAutoML is designed to democratize machine learning — enabling anyone (students, business analysts, domain experts) to build effective machine learning models without needing to master complex low-level engineering details.
✨ Key Features
🔬 Scientific Approach
1. Intelligent Preprocessing
- Automatic feature type detection (numeric, categorical, text)
- Adaptive missing value imputation (median / mode)
- StandardScaler & OneHotEncoder normalization
- ColumnTransformer pipeline preventing data leakage
2. Hyperparameter Tuning
- Grid Search & Random Search
- Bayesian Optimization (BO) & Genetic Algorithm (GA)
- $k$-fold cross-validation ($k=5$)
- Balancing accuracy vs compute efficiency
3. Multi-Criteria Evaluation
- Classification: Accuracy, Precision, Recall, F1, Balanced Acc
- Regression: MAE, MSE, RMSE, $R^2$ Score
- Generalization validation against overfitting
- Automated selection of champion model
Quickstart Guide
The fastest and most complete way to run Next.js, FastAPI, Worker cluster, MongoDB, MinIO, and Kafka:
# 1. Clone repository
git clone https://github.com/optivisionlab/AutoML.git
cd AutoML
# 2. Configure environment from templates
cp src/backend/temp.env src/backend/.env
cp src/frontend/temp.env src/frontend/.env
# 3. Launch full stack in background
docker-compose up -d --build
# To stop the system
docker-compose downMicroservices Architecture
┌─────────────────────────────────────────────────────────────┐
│ Frontend (Next.js) │
│ Web User Interface / Giao diện │
└────────────────────────────┬────────────────────────────────┘
│ HTTP/REST
┌────────────────────────────▼────────────────────────────────┐
│ Backend (FastAPI) │
│ API, Business Logic, Orchestration │
└─┬────────────┬──────────────┬─────────────┬─────────────────┘
│ │ │ │
│ │ │ │
┌─▼─┐ ┌────▼────┐ ┌────▼─────┐ ┌──▼───────┐
│ │ │ MongoDB │ │ Apache │ │ MinIO │
│ │ │(Database│ │ Kafka │ │ (Storage │
│ │ │ Metadata│ │ (Queue) │ │ Datasets)│
│ │ └─────────┘ └─────┬────┘ └──────────┘
│ │ │
│ └─────────────────────────┼─────────────────────┐
│ │ Task dispatch │
└─────────────────────────────┼─────────────────────┘
│
┌──────────▼──────────┐
│ Workers │
│ (Process Training │
│ Jobs from Kafka) │
└─────────────────────┘📋 Recent Release History
| Version | Date | Highlights | Status |
|---|---|---|---|
| v2.2.0 | 11/04/2026 | Distributed Computing, Smart Scheduling, Account Classification | Latest |
| v2.1.0 | 05/12/2025 | Optima Search (GA, Bayesian Optimization) | Supported |
| v2.0.0 | 19/10/2025 | MapReduce 1.0, MinIO Object Storage, Async API | Stable (ISINC 2026) |
| v1.1.2 | 21/06/2025 | UI Updates + Security Fixes | Supported |
| v1.1.0 | 03/06/2025 | Model Deployment & Inference API | Supported |
| v1.0.0 | 17/05/2025 | Initial Release - Nền tảng HAutoML | Initial Release |
👥 Contributors
GitHub ContributorsWe sincerely thank all contributors to the HAutoML project at OptiVisionLab:
HAutoML: Open-Source for Automated Machine Learning
Research published in Springer Nature ISINC 2026 by OptiVisionLab, School of ICT - Hanoi University of Industry.