Author: Sumit Thakur

With a few clicks in the Amazon SageMaker console or a few one-line API calls, you can now quickly search, filter, and sort your machine learning (ML) experiments using key model attributes, such as hyperparameter values and accuracy metrics, to help you more quickly identify the best models for your use case and get to […]

Data scientists and developers can now easily train machine learning models on datasets labeled by Amazon SageMaker Ground Truth. Amazon SageMaker Training now accepts the labeled datasets produced in augmented manifest format as input through both AWS Management Console and Amazon SageMaker Python SDK APIs. Last month during AWS re:Invent, we launched Amazon SageMaker Ground […]

The AWS Deep Learning AMIs for Ubuntu and Amazon Linux now come with an optimized build of TensorFlow 1.9 custom-built directly from source and fine-tuned for high performance training across Amazon EC2 instances. In addition, the AMIs come with the latest Apache MXNet 1.2 with several performance and usability improvements, the new Keras 2-MXNet backend […]

The AWS Deep Learning AMIs for Ubuntu and Amazon Linux now come pre-installed and fully configured with Horovod, the popular open source distributed training framework to scale TensorFlow training on multiple GPUs. This is an update to the optimized build of TensorFlow 1.8 that we launched in early May. This custom build of TensorFlow 1.8 […]

The AWS Deep Learning AMIs for Ubuntu and Amazon Linux now come with Chainer 4 and Microsoft Cognitive Toolkit (CNTK) 2.5.1 configured with optimizations for higher performance execution across Amazon EC2 instances.

The AWS Deep Learning AMIs for Ubuntu and Amazon Linux now come with TensorFlow 1.7, which is built with advanced optimizations for high-performance training across Amazon EC2 instance families. This is an update to the optimized build of TensorFlow 1.6 that we launched in late March. Faster training with optimized TensorFlow 1.7 The Amazon Machine […]

The AWS Deep Learning AMIs come with latest pip packages of popular deep learning frameworks pre-installed in separate virtual environments so that developers can quickly get started with training deep learning models. The new version of the Deep Learning AMIs for Ubuntu and Amazon Linux now come with TensorFlow 1.6, built with advanced optimizations for […]

The AWS Deep Learning AMIs provide fully-configured environments so that artificial intelligence (AI) developers and data scientists can quickly get started with deep learning models. The Amazon Machine Images (AMIs) now include Chainer (v3.4.0), a flexible and intuitive deep learning (DL) framework, as well as the latest versions of Apache MXNet and PyTorch. The Chainer define-by-run […]

The AWS Deep Learning AMIs for Ubuntu and Amazon Linux now include the latest versions of TensorFlow (1.5) and Microsoft Cognitive Toolkit (2.4). These frameworks provide support for NVIDIA CUDA 9 and cuDNN 7 drivers. This allows you to take advantage of the mixed-precision training supported by the V100 Volta GPUs powering Amazon EC2 P3 […]

The AWS Deep Learning AMIs help you quickly and easily get started with machine learning. The AMIs include a range of prebuilt options that cater to the diverse needs of machine learning practitioners. For those who want the latest stock versions of deep learning frameworks, the Deep Learning AMIs provide prebuilt pip binaries installed in […]