AWS artificial intelligence services enable enterprises to apply machine learning, natural language processing and other advanced technologies to their applications. Open up a vast number of computing possibilities with these AWS AI services and tools.
Machine learning relies on complex models that developers must train and tweak in response to expansive reservoirs of real-world data. This process can be painfully slow, expensive and filled with complications. Amazon SageMaker is a managed service intended to alleviate much of that complexity, but how exactly can enterprises use it?
Machine Learning with AWS :
The developers can launch a pre-built notebook, which AWS supplies for a variety of applications and use cases, then customize it according to the data set and schema the developer wants to train. Developers can also use custom-built algorithms written in one of the supported ML frameworks or any code that has been packaged as a Docker container image. SageMaker can pull data from Amazon Simple Storage Service (S3), and there is no practical limit to the size of the data set.
