Amazon Machine Learning vs Azure Machine Learning

Amazon Machine Learning
Amazon Machine Learning

58
79
0
Azure Machine Learning
Azure Machine Learning

63
81
0
Add tool

Amazon Machine Learning vs Azure Machine Learning: What are the differences?

Amazon Machine Learning: Visualization tools and wizards that guide you through the process of creating ML models w/o having to learn complex ML algorithms & technology. 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; Azure Machine Learning: 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.

Amazon Machine Learning and Azure Machine Learning can be primarily classified as "Machine Learning as a Service" tools.

Some of the features offered by Amazon Machine Learning are:

  • Easily Create Machine Learning Models
  • From Models to Predictions in Seconds
  • Scalable, High Performance Prediction Generation Service

On the other hand, Azure Machine Learning provides the following key features:

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

According to the StackShare community, Azure Machine Learning has a broader approval, being mentioned in 12 company stacks & 8 developers stacks; compared to Amazon Machine Learning, which is listed in 8 company stacks and 9 developer stacks.

- No public GitHub repository available -
- No public GitHub repository available -

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 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.

Want advice about which of these to choose?Ask the StackShare community!

Why do developers choose Amazon Machine Learning?
Why do developers choose Azure Machine Learning?
    Be the first to leave a pro
      Be the first to leave a pro
      What are the cons of using Amazon Machine Learning?
      What are the cons of using Azure Machine Learning?
        Be the first to leave a con
          Be the first to leave a con
          What companies use Amazon Machine Learning?
          What companies use Azure Machine Learning?

          Sign up to get full access to all the companiesMake informed product decisions

          What tools integrate with Amazon Machine Learning?
          What tools integrate with Azure Machine Learning?
            No integrations found
            What are some alternatives to Amazon Machine Learning and Azure Machine Learning?
            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.
            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.
            RapidMiner
            It is a software platform for data science teams that unites data prep, machine learning, and predictive model deployment.
            NanoNets
            Build a custom machine learning model without expertise or large amount of data. Just go to nanonets, upload images, wait for few minutes and integrate nanonets API to your application.
            See all alternatives
            Decisions about Amazon Machine Learning and Azure Machine Learning
            No stack decisions found
            Interest over time
            Reviews of Amazon Machine Learning and Azure Machine Learning
            No reviews found
            How developers use Amazon Machine Learning and Azure Machine Learning
            Avatar of Taylor Host
            Taylor Host uses Amazon Machine LearningAmazon Machine Learning

            Mild re-training data usage.

            How much does Amazon Machine Learning cost?
            How much does Azure Machine Learning cost?
            Pricing unavailable
            News about Amazon Machine Learning
            More news
            News about Azure Machine Learning
            More news