AWS Machine Learning Blog

Amazon’s own ‘Machine Learning University’ now available to all developers

Today, I’m excited to share that, for the first time, the same machine learning courses used to train engineers at Amazon are now available to all developers through AWS. We’ve been using machine learning across Amazon for more than 20 years. With thousands of engineers focused on machine learning across the company, there are very […]

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Amazon Rekognition announces updates to its face detection, analysis, and recognition capabilities

Today we are announcing updates to our face detection, analysis, and recognition features. These updates provide customers with improvements in the ability to detect more faces from images, perform higher accuracy face matches, and obtain improved age, gender, and emotion attributes for faces in images. Amazon Rekognition customers can use each of these enhancements starting […]

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Building a conversational business intelligence bot with Amazon Lex

Conversational interfaces are transforming the way people interact with software applications and services. They are untethering people from keyboards and smartphone gestures by replacing those interfaces with a more natural style of interaction: the spoken word. Increasingly, people are opting to interact with a bot when they need an answer to a question, to set […]

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New Features For Amazon SageMaker: Workflows, Algorithms, and Accreditation

We’ve seen a ton of progress in machine learning during the past 12 months, with customers using Amazon SageMaker – a fully-managed service which has put ML into the hands of tens of thousands of developers and data scientists – to find fraud, predict pitches, and tune engines. We’ve added nearly 100 new features and […]

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Amazon Transcribe now supports real-time transcriptions

Amazon Transcribe is an automatic speech recognition (ASR) service that makes it easy for developers to add speech-to-text capability to applications. We’re excited to announce a new feature called Streaming Transcription, which enables users to pass a live audio stream to our service and receive text transcripts in real time. Real-time transcriptions benefit use cases […]

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Easily monitor and visualize metrics while training models on Amazon SageMaker

Data scientists and developers can now quickly and easily access, monitor, and visualize metrics that are computed while training machine learning models on Amazon SageMaker. You can now specify the metrics you want to track by using the AWS Management Console for Amazon SageMaker or by using the Amazon SageMaker Python SDK APIs. After the […]

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Detect suspicious IP addresses with the Amazon SageMaker IP Insights algorithm

Today, we are announcing the new IP Insights algorithm for Amazon SageMaker. IP Insights is an unsupervised learning algorithm for detecting anomalous behavior and usage patterns of IP addresses. In this blog post, we introduce the problem of identifying fraudulent behavior using IP addresses, describe the Amazon SageMaker IP Insights algorithm, demonstrate how you can use it in […]

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Analyze live video at scale in real time using Amazon Kinesis Video Streams and Amazon SageMaker

We are excited to announce the launch of the Amazon Kinesis Video Streams Inference Template (KIT) for Amazon SageMaker. This capability enables customers to attach Kinesis Video streams to Amazon SageMaker endpoints in minutes. This drives real-time inferences without having to use any other libraries or write custom software to integrate the services. The KIT comprises […]

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Amazon SageMaker Automatic Model Tuning becomes more efficient with warm start of hyperparameter tuning jobs

Earlier this year, we launched Amazon SageMaker Automatic Model Tuning, which allows developers and data scientists to save significant time and effort in training and tuning their machine learning models. Today, we are launching warm start of hyperparameter tuning jobs in Automatic Model Tuning. Data scientists and developers can now create a new hyperparameter tuning […]

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Build Your Own Natural Language Models on AWS (no ML experience required)

At AWS re:Invent last year we announced Amazon Comprehend, a natural language processing service which extracts key phrases, places, peoples’ names, brands, events, and sentiment from unstructured text. Comprehend – which is powered by sophisticated deep learning models trained by AWS – allows any developer to add natural language processing to their applications without requiring […]

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