Amazon SageMaker is the AWS one stop shop for all your Data Science and Machine Learning needs. Sagemaker allows you to prepare your data as well as build, train, tune and deploy your machine learning models. It's clear to see why its one of our go-to tools.
Through its Studio Notebooks, SageMaker allows users to create Jupyter notebooks with a single click. These notebooks are all managed, elastic and scalable so you can easily take full advantage of the scalability of AWS.
SageMaker comes with many of the most common algorithms built in, requiring little code to get started. However if The algorithm you wish to use is not built in, thats no problem as SageMaker supports the most popular ML frameworks (such as Tensorflow) using script mode. You can even use State of the art (SOTA) cutting edge models (such as Catboost) coded up and trained by you, then deployed using a Docker container.
SageMaker brings the rigour of data engineering to the ML space, allowing users to benefit from detailed audit trails and testing.
Check out our helpful blogs on everything SageMaker below.
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