Getting started with Sematic in 5 minutes

Sematic is an open-source development platform tailored for machine learning and data science, allowing users to efficiently build end-to-end ML pipelines that can be executed locally or in cloud environments. With support for integrations like PyTorch, Kubernetes, and Snowflake, it accommodates complex pipelines of Python-defined business logic across diverse computing resources. The platform's components include a lightweight Python SDK, an execution backend for local or Kubernetes orchestration, a command-line interface, and a web dashboard, with advanced features like run caching and fault tolerance. Sematic functions, which form the core of pipeline operations, are Python functions decorated to enable serialization and tracking, with their execution state monitored and visualized in a dashboard. The platform supports Python versions 3.8 to 3.10 on Linux and Mac, and can be installed via pip, with a web dashboard accessible through a local server. Sematic facilitates the iterative development and debugging of pipelines on local machines before deploying them to cloud environments, providing features such as step retries, pipeline nesting, and artifact visualization to enhance the user experience.