AWS Machine Learning Blog

Tag: Deep Learning AMI

Faster training with optimized TensorFlow 1.6 on Amazon EC2 C5 and P3 instances

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 […]

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AWS Deep Learning AMIs now support Chainer and latest versions of PyTorch and Apache MXNet

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 […]

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AWS Deep Learning AMIs Now Provide Faster Training on Volta GPUs for TensorFlow and Microsoft Cognitive Toolkit

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 […]

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Zocdoc builds patient confidence using TensorFlow on AWS

The healthcare industry is complicated. A recent survey showed that more than half of Americans have difficulty understanding their insurance coverage, and three-quarters want an easier way to check if doctors are in-network. Zocdoc helps patients navigate this maze, allowing individuals with health care needs to make more informed choices and find care that matches […]

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AWS Deep Learning AMIs now come with TensorFlow 1.5 and new Model Serving capabilities

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 […]

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AWS Deep Learning AMIs Now Available in 4 New Regions: Beijing, Frankfurt, Singapore, and Mumbai

The AWS Deep Learning AMIs are now available in four new AWS Regions: China (Beijing) operated by Sinnet, Europe (Frankfurt), Asia Pacific (Singapore), and Asia Pacific (Mumbai). The Amazon Machine Images (AMIs) provide provide machine learning practitioners with the infrastructure and tools to accelerate deep to quickly start experimenting with deep learning models. The AMIs […]

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Updated AWS Deep Learning AMIs: New Versions of TensorFlow, Apache MXNet, Keras, and PyTorch

We’re excited to update the AWS Deep Learning AMIs with significantly faster training on NVIDIA Tesla V100 “Volta” GPUs across many frameworks, including TensorFlow, PyTorch, Keras, and the latest Apache MXNet 1.0 release. There are two main flavors of the AMIs available today. The Conda-based AWS Deep Learning AMI packages the latest point releases of […]

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Building an Autonomous Vehicle, Part 4:  Using Behavioral Cloning with Apache MXNet for Your Self-Driving Car

In the first blog post of our autonomous vehicle series, you built your Donkey vehicle and deployed your pilot server onto an Amazon EC2 instance. In the second blog post, you learned to drive the Donkey car, and the Donkey car learned to self-drive. In the third blog post, you learned about the process of streaming telemetry […]

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New AWS Deep Learning AMIs for Machine Learning Practitioners

We’re excited to announce the availability of two new versions of the AWS Deep Learning AMI. The first is a Conda-based AMI with separate Python environments for deep learning frameworks created using Conda—a popular open source package and environment management tool. The second is a Base AMI with GPU drivers and libraries to deploy your own […]

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