Amazon SageMaker vs GraphLab Create

Amazon SageMaker vs GraphLab Create: What are the differences?

Amazon SageMaker: Accelerated Machine Learning. A fully-managed service that enables developers and data scientists to quickly and easily build, train, and deploy machine learning models at any scale; GraphLab Create: Machine learning platform that enables data scientists and app developers to easily create intelligent apps at scale. 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.

Amazon SageMaker and GraphLab Create belong to "Machine Learning as a Service" category of the tech stack.

Some of the features offered by Amazon SageMaker are:

• 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

On the other hand, GraphLab Create provides the following key features:

• Analyze terabyte scale data at interactive speeds, on your desktop.
• A Single platform for tabular data, graphs, text, and images.
• State of the art machine learning algorithms including deep learning, boosted trees, and factorization machines.