3 dépôts
Distributed workflows for creating and scaling predictive analytics models.
Distinct from Scalability Management: Focuses on the model development workflow rather than general infrastructure resource allocation
Explore 3 awesome GitHub repositories matching devops & infrastructure · Predictive Model Workflows. Refine with filters or upvote what's useful.
Apache Spark is a unified distributed data processing engine designed for large-scale data analysis and computation graphs. It functions as a distributed machine learning framework, a graph processing system, a real-time stream processor, and a SQL analytics engine. The system enables the execution of distributed SQL querying, large-scale graph analysis, and real-time stream analytics across clusters of machines. It also provides a scalable environment for implementing machine learning algorithms and predictive model development on massive datasets. The engine incorporates relational query e
Implements scalable algorithms and workflows to build predictive analytics models on massive datasets.
Minds Platform is an automation system and application platform designed for building and deploying custom AI tools and workflows. It functions as a machine learning integration layer and self-hosted orchestrator that connects predictive models and large language models to external data sources. The platform enables the execution of multi-step tasks that read and write data to automate reports and operational activities. It supports deployment across cloud, on-premises, and virtual private cloud environments to maintain control over models and data. Capabilities include event-driven workflow
Connects machine learning models directly to data sources to automate analytics and create data-driven workflows.
Routes prediction results to downstream automation nodes for CRM updates or alerting.