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Amazon SageMaker Neo – Train Your Machine Learning Models Once, Run Them Anywhere

Machine learning (ML) is split in two distinct phases: training and inference. Training deals with building the model, i.e. running a ML algorithm on a dataset in order to identify meaningful patterns. This often requires large amounts…
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Amazon Forecast – Time Series Forecasting Made Easy

The capacity to foresee the future would be an incredible superpower. At AWS, we can’t give you that, but we can help you use machine learning to forecast time series in a few steps.The goal of time series forecasting is to predict…
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Amazon Personalize – Real-Time Personalization and Recommendation for Everyone

Machine learning definitely offers a wide range of exciting topics to work on, but there’s nothing quite like personalization and recommendation.At first glance, matching users to items that they may like sounds like a simple problem.…
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Amazon SageMaker RL – Managed Reinforcement Learning with Amazon SageMaker

In the last few years, machine learning (ML) has generated a lot of excitement. Indeed, from medical image analysis to self-driving trucks, the list of complex tasks that ML models can successfully accomplish keeps growing, but what makes…
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Amazon SageMaker Ground Truth – Build Highly Accurate Datasets and Reduce Labeling Costs by up to 70%

In 1959, Arthur Samuel defined machine learning as a “field of study that gives computers the ability to learn without being explicitly programmed”. However, there is no deus ex machina: the learning process requires an algorithm…
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Amazon Elastic Inference – GPU-Powered Deep Learning Inference Acceleration

One of the reasons for the recent progress of Artificial Intelligence and Deep Learning is the fantastic computing capabilities of Graphics Processing Units (GPU). About ten years ago, researchers learned how to harness their massive hardware…
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Amazon Comprehend Medical – Natural Language Processing for Healthcare Customers

As the son of a Gastroenterologist and a Dermatologist, I grew up listening to arcane conversations involving a never-ending stream of complex medical terms: human anatomy, surgical procedures, medication names… and their abbreviations.…
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Amazon SageMaker Adds Batch Transform Feature and Pipe Input Mode for TensorFlow Containers

At the New York Summit a few days ago we launched two new Amazon SageMaker features: a new batch inference feature called Batch Transform that allows customers to make predictions in non-real time scenarios across petabytes of data and…
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Amazon Translate Adds Support for Japanese, Russian, Italian, Traditional Chinese, Turkish, and Czech

Today I’m excited to announce that Amazon Translate has added support for Japanese, Russian, Italian, Traditional Chinese, Turkish, and Czech! Amazon Translate is a translation API that delivers fast, high-quality, and affordable…
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Amazon Kinesis Video Streams Adds Support For HLS Output Streams

Today I’m excited to announce and demonstrate the new HTTP Live Streams (HLS) output feature for Amazon Kinesis Video Streams (KVS). If you’re not already familiar with KVS, Jeff covered the release for AWS re:Invent in 2017.…