SageMaker Ground Truth helps you build highly accurate training datasets quickly. The service offers easy access to your own and third-party human labelers and provides them with built-in workflows and
Introducing Amazon SageMaker Studio – the first integrated development environment (IDE) for machine learning
There are a lot of components to machine learning workflows, many of which come with their own set of tools that exist separately. Switching between multiple different tools and user
In addition to the new features brought by the v0.9 framework, this new SageMaker release offers customers: Flexibility: This new release of XGBoost algorithm can be used as a built-in
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. SageMaker includes hosted Jupyter
You can now compare and view differences between two notebooks that are version controlled with Git in SageMaker. Jupyter notebooks (which SageMaker notebooks are built upon) are stored as JSON
Introducing Amazon SageMaker ml.p3dn.24xlarge instances, optimized for distributed machine learning with up to 4x the network bandwidth of ml.p3.16xlarge instances
The ml.p3dn.24xlarge instances provide up to 100 Gbps of networking throughput, 96 custom Intel® Xeon® Scalable (Skylake) vCPUs, 8 NVIDIA® V100 Tensor Core GPUs with 32 GB of memory each,
Amazon SageMaker Now Supports More Refined Access Control using Amazon SageMaker-specific Condition Keys
You can use Amazon SageMaker-specific condition keys to enforce best practices and compliance requirements. This includes encryption of data, encryption of storage volumes, network isolation, and controlled access to Amazon
Amazon SageMaker now supports accelerated training with new, smaller, Amazon FSx for Lustre file systems
Amazon FSx for Lustre is a high performance file system that works with Amazon S3 data and is optimized for workloads such as machine learning, analytics, and high performance computing.
With this launch, you no longer need to log into your notebook terminal to access logs and can instead view and analyze the logs directly from CloudWatch. You can use
Amazon SageMaker Now Works With Amazon FSx For Lustre and Amazon EFS, Accelerating And Simplifying Model Training
Until today, Amazon SageMaker transparently downloaded a full training set from Amazon S3 to local file storage at the start of a training job, when using the File input mode.