"The deployment is very good, where you only need to press a few buttons."
"The key feature is the automated model-building. It has a good UI that will let people who aren't data scientists get in there and upload datasets and actually start building models, with very little training. They don't need to have any understanding of data science."
Amazon SageMaker is a fully-managed platform that enables developers and data scientists to quickly and easily build, train, and deploy machine learning models at any scale. Amazon SageMaker removes all the barriers that typically slow down developers who want to use machine learning.
SparkCognition builds leading artificial intelligence solutions to advance the most important interests of society. We help customers analyze complex data, empower decision making, and transform human and industrial productivity with award-winning machine learning technology and expert teams focused on defense, IIoT, and finance.
Amazon SageMaker is ranked 9th in Data Science Platforms with 1 review while Darwin is ranked 10th in Data Science Platforms with 1 review. Amazon SageMaker is rated 7.0, while Darwin is rated 10.0. The top reviewer of Amazon SageMaker writes "Good deployment and monitoring features, but the interface could use some improvement". On the other hand, the top reviewer of Darwin writes "Empowers SMEs to build solutions and interface them with the existing business systems, products and workflows". Amazon SageMaker is most compared with Databricks, Microsoft Azure Machine Learning Studio, Dataiku Data Science Studio, Domino Data Science Platform and Anaconda, whereas Darwin is most compared with Microsoft Azure Machine Learning Studio, Databricks, IBM Watson Studio and Dataiku Data Science Studio.
See our list of best Data Science Platforms vendors.
We monitor all Data Science Platforms reviews to prevent fraudulent reviews and keep review quality high. We do not post reviews by company employees or direct competitors. We validate each review for authenticity via cross-reference with LinkedIn, and personal follow-up with the reviewer when necessary.