Showing 2 open source projects for "machine learning regression"

View related business solutions
  • AI-powered service management for IT and enterprise teams Icon
    AI-powered service management for IT and enterprise teams

    Enterprise-grade ITSM, for every business

    Give your IT, operations, and business teams the ability to deliver exceptional services—without the complexity. Maximize operational efficiency with refreshingly simple, AI-powered Freshservice.
    Try it Free
  • Stop Cyber Threats with VM-Series Next-Gen Firewall on Azure Icon
    Stop Cyber Threats with VM-Series Next-Gen Firewall on Azure

    Native application identity and user-based security for your Azure cloud

    Gain integrated visibility across all traffic in a single pass. Deploy Palo Alto Networks VM-Series to determine application identity and content while automating security policy updates via rich APIs.
    Get a free trial
  • 1
    Apache Spark

    Apache Spark

    A unified analytics engine for large-scale data processing

    Apache Spark is a unified engine for large-scale data processing, offering APIs for batch jobs, streaming, machine learning, and graph computation. It builds on resilient distributed datasets (RDDs) and the newer DataFrame/Dataset abstractions to provide fault-tolerant, in-memory computation across clusters. Spark’s execution engine handles scheduling, shuffles, caching, and data locality so users can focus on transformations rather than infrastructure plumbing.
    Downloads: 11 This Week
    Last Update:
    See Project
  • 2
    Apache PredictionIO

    Apache PredictionIO

    Machine learning server for developers and ML engineers

    Apache PredictionIO® is an open source Machine Learning Server built on top of a state-of-the-art open source stack for developers and data scientists to create predictive engines for any machine learning task. Quickly build and deploy an engine as a web service on production with customizable templates; respond to dynamic queries in real-time once deployed as a web service; evaluate and tune multiple engine variants systematically; unify data from multiple platforms in batch or in real-time for comprehensive predictive analytics; speed up machine learning modeling with systematic processes and pre-built evaluation measures; support machine learning and data processing libraries such as Spark MLLib and OpenNLP; implement your own machine learning models and seamlessly incorporate them into your engine; simplify data infrastructure management.
    Downloads: 0 This Week
    Last Update:
    See Project
  • Previous
  • You're on page 1
  • Next
Auth0 Logo