Search Results for "processmaker-processmaker-3.5.7-community*"

...Regularised linear models with Stochastic Gradient Descent provide a fast and accurate prediction. Scalable and flexible. Python-based implementation is easy to integrate into existing pipelines. A community-driven encyclopedia for cell types.

Apache DevLake is an open-source dev data platform that ingests, analyzes, and visualizes the fragmented data from DevOps tools to extract insights for engineering excellence, developer experience, and community growth. Apache DevLake is designed for developer teams looking to make better sense of their development process and to bring a more data-driven approach to their own practices. You can ask Apache DevLake many questions regarding your development process. Just connect and query. Your Dev Data lives in many silos and tools. DevLake brings them all together to give you a complete view of your Software Development Life Cycle (SDLC). ...

...In order to run a test instance of PANDORA, users will first need to prepare their local environment by downloading, installing, and configuring Docker. genular is a community behind SIMON an open-source Machine Learning KnowledgeDiscovery software, built by a vibrant community of people just like you! Join us and make SIMON even cooler! Exploratory analysis of machine learning results with the help of many different visualization techniques will give you instant insights into models and data.

Nest Manager is a community SmartThings solution that integrates Nest devices—thermostats, Protects, and cameras—into the SmartThings ecosystem via a comprehensive SmartApp and device handlers. It offers a unified dashboard, rich device tiles, and automation hooks so users can monitor and control temperature, modes, and alerts alongside other smart home devices.

COMA CE is the community edition of the well-established COMA project developed at the University of Leipzig. It comprises the parsers, matcher library, matching framework and a sample GUI for tests and evaluations. COMA was initiated at the database chair of the University of Leipzig in 2002 and got much positive feedback ever since. It excels due to numerous matching strategies, which can be combined to large matching workflows, and which enable reliable match results between different kind of schemas.

This disease-centric project contributes data integration and analysis tools from the Institute for Systems Biology (ISB). We offer this project to the research community to further our efforts in disease prediction and prevention.