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Top 9 DevOps Tools in Data Science And Machine Learning

The best DevOps Tools within the Data Science And Machine Learning category - based on our collection of reviews & verified products.

HHVM Mesosphere DCOS Metaflow AWS Chatbot Activeeon Azure Machine Learning Studio Kazuhm AWS Data Wrangler

Summary

The top products on this list are HHVM, Mesosphere DCOS, and Metaflow. All products here are categorized as: Tools and platforms that facilitate DevOps practices in software development. Platforms and tools for data analysis, scientific research, and machine learning applications. One of the criteria for ordering this list is the number of mentions that products have on reliable external sources. You can suggest additional sources through the form here.
  1. 1
    HHVM is an open-source virtual machine designed for executing programs written in Hack and PHP.
    Pricing:
    • Open Source

    #Cloud Computing #DevOps Tools #Continuous Integration And Delivery 6 social mentions

  2. Mesosphere DCOS organizes your entire infrastructure as if it was a single computer.

    #Cloud Computing #DevOps Tools #Developer Tools

  3. Framework for real-life data science; build, improve, and operate end-to-end workflows.
    Pricing:
    • Open Source

    #Automation #Workflow Automation #Web Service Automation 14 social mentions

  4. AWS Chatbot is an interactive agent that makes it easy to monitor and interact with your AWS resources from your team chat room. Learn more about the key benefits and how it works.

    #Dev Ops #DevOps Tools #AWS Tools 6 social mentions

  5. ProActive Workflows & Scheduling is a java-based cross-platform workflow scheduler and resource manager that is able to run workflow tasks in multiple languages and multiple environments: Windows, Linux, Mac, Unix, etc.

    #Automation #DevOps Tools #Workflow Automation

  6. Pipelines Inc.

    #DevOps Tools #Code Collaboration #Continuous Deployment

  7. Azure Machine Learning Studio is a GUI-based integrated development environment for constructing and operationalizing Machine Learning workflow on Azure.

    #Data Science And Machine Learning #Machine Learning #AI 2 social mentions

  8. 8
    Manage your containerized workloads through Kazuhm's easy to use distributed computing technology. Kazuhm saves cloud costs, improves security and latency.
    Pricing:
    • Freemium
    • Free Trial

    #Cloud Computing #SaaS #Cloud Infrastructure

  9. Pandas on AWS. Contribute to awslabs/aws-data-wrangler development by creating an account on GitHub.

    #Form Builder #DevOps Tools #Checklists 4 social mentions

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