Amazon SageMaker vs Azure Machine Learning vs GraphLab Create

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Amazon SageMaker

193
216
+ 1
0
Azure Machine Learning

196
283
+ 1
0
GraphLab Create

6
34
+ 1
3
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Pros of Amazon SageMaker
Pros of Azure Machine Learning
Pros of GraphLab Create
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        Intelligent Function Defaults
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        Fast Data Summary
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        Simple Machine Learning Tools

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      What is 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.

      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 GraphLab Create?

      Building an intelligent, predictive application involves iterating over multiple steps: cleaning the data, developing features, training a model, and creating and maintaining a predictive service. GraphLab Create does all of this in one platform. It is easy to use, fast, and powerful.

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      What companies use Amazon SageMaker?
      What companies use Azure Machine Learning?
      What companies use GraphLab Create?
        No companies found

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        What tools integrate with Amazon SageMaker?
        What tools integrate with Azure Machine Learning?
        What tools integrate with GraphLab Create?
          No integrations found

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          What are some alternatives to Amazon SageMaker, Azure Machine Learning, and GraphLab Create?
          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.
          Kubeflow
          The Kubeflow project is dedicated to making Machine Learning on Kubernetes easy, portable and scalable by providing a straightforward way for spinning up best of breed OSS solutions.
          TensorFlow
          TensorFlow is an open source software library for numerical computation using data flow graphs. Nodes in the graph represent mathematical operations, while the graph edges represent the multidimensional data arrays (tensors) communicated between them. The flexible architecture allows you to deploy computation to one or more CPUs or GPUs in a desktop, server, or mobile device with a single API.
          IBM Watson
          It combines artificial intelligence (AI) and sophisticated analytical software for optimal performance as a "question answering" machine.
          See all alternatives