Azure Machine Learning vs Restlet Studio

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Azure Machine Learning

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Restlet Studio

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Azure Machine Learning vs Restlet Studio: What are the differences?

Developers describe Azure Machine Learning as "A fully-managed cloud service for predictive analytics". Azure Machine Learning is a fully-managed cloud service that enables data scientists and developers to efficiently embed predictive analytics into their applications, helping organizations use massive data sets and bring all the benefits of the cloud to machine learning. On the other hand, Restlet Studio is detailed as "The first browser-based IDE for APIs". Packaged as a Chrome extension and accessible from any modern web browser, Restlet Studio instantly provides to any developer powerful API crafting capabilities. Through an intuitive interface, developers can visually define all the elements of a web API, and automatically generate the client SDK and server skeleton of their API.

Azure Machine Learning can be classified as a tool in the "Machine Learning as a Service" category, while Restlet Studio is grouped under "API Tools".

Some of the features offered by Azure Machine Learning are:

  • Designed for new and experienced users
  • Proven algorithms from MS Research, Xbox and Bing
  • First class support for the open source language R

On the other hand, Restlet Studio provides the following key features:

  • Visual Crafting of APIs
  • RESTful APIs Made Easy
  • No Wasted Configuration Time
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Pros of Azure Machine Learning
Pros of Restlet Studio
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      Powerful & intuitive API designer
    • 1
      GitHub Integration
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      Easy to used

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    Cons of Azure Machine Learning
    Cons of Restlet Studio
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        Opaque Pricing Model

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      What is Azure Machine Learning?

      Azure Machine Learning is a fully-managed cloud service that enables data scientists and developers to efficiently embed predictive analytics into their applications, helping organizations use massive data sets and bring all the benefits of the cloud to machine learning.

      What is Restlet Studio?

      Packaged as a Chrome extension and accessible from any modern web browser, Restlet Studio instantly provides to any developer powerful API crafting capabilities. Through an intuitive interface, developers can visually define all the elements of a web API, and automatically generate the client SDK and server skeleton of their API.

      Need advice about which tool to choose?Ask the StackShare community!

      What companies use Azure Machine Learning?
      What companies use Restlet Studio?
      See which teams inside your own company are using Azure Machine Learning or Restlet Studio.
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      What tools integrate with Azure Machine Learning?
      What tools integrate with Restlet Studio?
        No integrations found
        What are some alternatives to Azure Machine Learning and Restlet Studio?
        Python
        Python is a general purpose programming language created by Guido Van Rossum. Python is most praised for its elegant syntax and readable code, if you are just beginning your programming career python suits you best.
        Azure Databricks
        Accelerate big data analytics and artificial intelligence (AI) solutions with Azure Databricks, a fast, easy and collaborative Apache Spark–based analytics service.
        Amazon SageMaker
        A fully-managed service that enables developers and data scientists to quickly and easily build, train, and deploy machine learning models at any scale.
        Amazon Machine Learning
        This new AWS service helps you to use all of that data you’ve been collecting to improve the quality of your decisions. You can build and fine-tune predictive models using large amounts of data, and then use Amazon Machine Learning to make predictions (in batch mode or in real-time) at scale. You can benefit from machine learning even if you don’t have an advanced degree in statistics or the desire to setup, run, and maintain your own processing and storage infrastructure.
        Databricks
        Databricks Unified Analytics Platform, from the original creators of Apache Spark™, unifies data science and engineering across the Machine Learning lifecycle from data preparation to experimentation and deployment of ML applications.
        See all alternatives