Ploomber
YAML-based pipeline builder for ML models
Ploomber is an open-source workflow management tool designed for data science and machine learning projects. It simplifies the development and deployment of machine learning models by providing a flexible and easy-to-use framework for creating reproducible workflows. With Ploomber, users can define complex pipelines that incorporate data ingestion, transformation, model training, and deployment. The pipelines are defined using a simple YAML-based configuration file, and each step in the pipeline is defined as a separate script or notebook. This approach provides a high degree of flexibility and makes it easy to add new steps or modify existing ones as needed. One of the key features of Ploomber is its ability to integrate with popular data science tools like Jupyter Notebooks and Apache Airflow. This allows users to leverage their existing skills and workflows while taking advantage of the benefits of Ploomber's reproducibility and automation. Ploomber also provides a range of built-in features that simplify common data science tasks. For example, it includes support for data versioning and automatic re-execution of failed tasks. It also provides a built-in scheduler that can be used to automatically run the pipeline on a regular schedule. Overall, Ploomber is a powerful and flexible workflow management tool that is well-suited for data science and machine learning projects. Its open-source architecture and active community make it a cost-effective alternative to commercial ML Ops solutions.