Amazon SageMaker vs Azure Machine Learning vs BigML
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Detailed Comparison
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. | 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. | A fully-managed service that enables developers and data scientists to quickly and easily build, train, and deploy machine learning models at any scale. |
Designed for new and experienced users;Proven algorithms from MS Research, Xbox and Bing;First class support for the open source language R;Seamless connection to HDInsight for big data solutions;Deploy models to production in minutes;Pay only for what you use. No hardware or software to buy | REST API; bindings in Pyton, Java, Ruby, node.js, C#, Clojure, PHP, and more; several algorithms, including categorical & regression decision trees, ensembles of trees (random decision forest), cluster analysis and more; models are fully actionable -- translated into code that can be cut/paste for local utilization; PredictServer (and Amazon AMI) can be used for real-time or large batch predictions; models can be shared privately or publicly (for free or for a fee set by the developer) | Build: managed notebooks for authoring models, built-in high-performance algorithms, broad framework support; Train: one-click training, authentic model tuning; Deploy: one-click deployment, automatic A/B testing, fully-managed hosting with auto-scaling |
Statistics | ||
Stacks 241 | Stacks 14 | Stacks 295 |
Followers 373 | Followers 29 | Followers 284 |
Votes 0 | Votes 1 | Votes 0 |
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