ML (Machine Learning) makes it possible to accomplish business goals by manipulating information collected from a server. SageMaker Neo is an Amazon Web Services machine learning(ML) resource that makes it easier to use artificial intelligence to super power your business production through smarter predictions. You’ll save time and still be accurate when using your ML training models. Neo is automatically optimized to give you double the operating power for use on any ML framework and target hardware platform. The open source documentation gives developers the ability to open the hood of Neo and customize their ML environment. Neo offers numerous benefits that can be used on any server.
Highly accurate training datasets built by machine learning that saves up to 70% of labeling costs AWS SageMaker Ground Truth is a resource for building high-quality training datasets for machine learning. You will be able to provide human and public labelers with built-in workflows and interfaces for common labeling tasks. Data is eventually labeled automatically, …
Amazon’s AWS SageMaker makes it possible to build, train and deploy machine learning models quickly. It is fully managed and covers the entire ML (machine learning) workflow. A lot of large companies use SageMaker resource. With SageMaker you can; collect and prepare training data, choose and optimize your ML algorithms, setup and manage training environments, and tune your model for optimization. Models can be deployed and managed in production. Use reinforcement learning to build smart outcomes. SageMaker is open and flexible and AWS will provide detailed instructions on how to use the SageMaker resource.