👋 Introduction
This is the documentation of dstack, an open-source Python library for building data and ML applications. Both the library and the documentation are licensed under Apache 2.0.
dstack is the easiest way of building data and ML applications for non-technical colleagues within the company. dstack helps build internal in-house data applications, e.g. for quick prototypes of ML models, or for advanced analysis or prediction in business units as an addition to normal business intelligence tools (Tableau, Power BI, QuilkSense, Metabase, Superset, etc).
dstack can be easily run locally or over containers. It can be deployed to dedicated servers or to any cloud. Deployment of dstack applications is done with a few lines of Python code. It can be done either from scripts or from Jupyter notebooks. Once a dstack application is deployed, you can immediately invite other users to work with it.
