Amazon Machine Learning vs Amazon SageMaker vs BigML

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Amazon Machine Learning

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Amazon SageMaker

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BigML

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Pros of Amazon Machine Learning
Pros of Amazon SageMaker
Pros of BigML
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        Ease of use, great REST API and ML workflow automation

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      What is 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.

      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 BigML?

      BigML provides a hosted machine learning platform for advanced analytics. Through BigML's intuitive interface and/or its open API and bindings in several languages, analysts, data scientists and developers alike can quickly build fully actionable predictive models and clusters that can easily be incorporated into related applications and services.

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      What companies use Amazon Machine Learning?
      What companies use Amazon SageMaker?
      What companies use BigML?

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      What tools integrate with Amazon Machine Learning?
      What tools integrate with Amazon SageMaker?
      What tools integrate with BigML?
        No integrations found
          No integrations found

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          What are some alternatives to Amazon Machine Learning, Amazon SageMaker, and BigML?
          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.
          Apache Spark
          Spark is a fast and general processing engine compatible with Hadoop data. It can run in Hadoop clusters through YARN or Spark's standalone mode, and it can process data in HDFS, HBase, Cassandra, Hive, and any Hadoop InputFormat. It is designed to perform both batch processing (similar to MapReduce) and new workloads like streaming, interactive queries, and machine learning.
          RapidMiner
          It is a software platform for data science teams that unites data prep, machine learning, and predictive model deployment.
          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.
          Algorithms.io
          Build And Run Predictive Applications For Streaming Data From Applications, Devices, Machines and Wearables
          See all alternatives