dessa-oss/atlas
📦 Open Source Projectdessa-oss
An open-source, self-hosted platform designed to streamline applied deep learning development and model management.
Atlas is a comprehensive, self-hosted platform engineered to tackle the complexities of applied deep learning development. It serves as a centralized hub for managing the entire machine learning lifecycle, from initial experimentation to production deployment. Designed with a focus on flexibility and control, Atlas allows teams to maintain their infrastructure while benefiting from structured model management, versioning, and tracking capabilities.
Key technical features include robust support for GPU-accelerated workflows, enabling efficient training and inference cycles. The platform emphasizes reproducibility, ensuring that data scientists can track experiments, hyperparameters, and model artifacts with ease. By providing a unified interface for model management, Atlas reduces the overhead associated with manual tracking and environment configuration. It is built to integrate seamlessly into existing Python-based data science stacks, making it an ideal choice for organizations looking to standardize their deep learning development processes without relying on proprietary, cloud-locked services.
💡Highlights
- ├─Self-hosted deep learning platform
- ├─Centralized model lifecycle management
- └─GPU-optimized development workflows
🎯For
- ├─Data Scientists
- ├─Machine Learning Engineers
- └─MLOps Practitioners