Search Results for "apache server"

ClearML is an open source platform that automates and simplifies developing and managing machine learning solutions for thousands of data science teams all over the world. It is designed as an end-to-end MLOps suite allowing you to focus on developing your ML code & automation, while ClearML ensures your work is reproducible and scalable. The ClearML Python Package for integrating ClearML into your existing scripts by adding just two lines of code, and optionally extending your experiments...

Python command line tool and Python engine to label table fields and fields in data files. It could help to find meaningful data in your tables and data files or to find Personal identifiable information (PII). Metacrafter is a rule-based tool that helps to label fields of the tables in databases. It scans table and finds person names, surnames, midnames, PII data, basic identifiers like UUID/GUID. These rules written as .yaml files and could be easily extended.

Serve machine learning models within a Docker container using Amazon SageMaker. Amazon SageMaker is a fully managed service for data science and machine learning (ML) workflows. You can use Amazon SageMaker to simplify the process of building, training, and deploying ML models. Once you have a trained model, you can include it in a Docker container that runs your inference code. A container provides an effectively isolated environment, ensuring a consistent runtime regardless of where the...

Bloxs is a simple Python package that helps you display information in an attractive way (formed in blocks). Perfect for building dashboards, reports and apps in the notebook.

GeoNotebook is an open-source extension to the Jupyter Notebook ecosystem that equips users with powerful geospatial visualization and analysis capabilities directly within the notebook interface. It integrates with GeoJS and other geospatial services to enable rich, interactive map rendering, layer control, and GIS data manipulation alongside traditional code and markdown cells in a Jupyter environment. Users can execute Python geospatial analysis and immediately visualize results on slippy...