AWS Machine Learning Blog

Category: Artificial Intelligence

Optimizing applications with EagleDream in Amazon CodeGuru Profiler

This is a guest post by Dustin Potter at EagleDream Technologies. In their own words, “EagleDream Technologies educates, enables, and empowers the world’s greatest companies to use cloud-native technology to transform their business. With extensive experience architecting workloads on the cloud, as well as a full suite of skills in application modernization, data engineering, data […]

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Amazon Translate ranked as #1 machine translation provider by Intento

Customer obsession, one of the key Amazon Leadership principles that guides everything we do at Amazon, has helped Amazon Translate be recognized as an industry leading neural machine translation provider. This year, Intento ranked Amazon Translate #1 on the list of top-performing machine translation providers in its The State of Machine Translation 2020 report. We are […]

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Building a medical image search platform on AWS

Improving radiologist efficiency and preventing burnout is a primary goal for healthcare providers. A nationwide study published in Mayo Clinic Proceedings in 2015 showed radiologist burnout percentage at a concerning 61% [1]. In additon, the report concludes that “burnout and satisfaction with work-life balance in US physicians worsened from 2011 to 2014. More than half […]

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Streamlining data labeling for YOLO object detection in Amazon SageMaker Ground Truth

Object detection is a common task in computer vision (CV), and the YOLOv3 model is state-of-the-art in terms of accuracy and speed. In transfer learning, you obtain a model trained on a large but generic dataset and retrain the model on your custom dataset. One of the most time-consuming parts in transfer learning is collecting […]

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Using speaker diarization for streaming transcription with Amazon Transcribe and Amazon Transcribe Medical

Conversational audio data that requires transcription, such as phone calls, doctor visits, and online meetings, often has multiple speakers. In these use cases, it’s important to accurately label the speaker and associate them to the audio content delivered. For example, you can distinguish between a doctor’s questions and a patient’s responses in the transcription of […]

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Optimizing the cost of training AWS DeepRacer reinforcement learning models

AWS DeepRacer is a cloud-based 3D racing simulator, an autonomous 1/18th scale race car driven by reinforcement learning, and a global racing league. Reinforcement learning (RL), an advanced machine learning (ML) technique, enables models to learn complex behaviors without labeled training data and make short-term decisions while optimizing for longer-term goals. But as we humans can attest, learning something […]

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Using log analysis to drive experiments and win the AWS DeepRacer F1 ProAm Race

This is a guest post by Ray Goh, a tech executive at DBS Bank.  AWS DeepRacer is an autonomous 1/18th scale race car powered by reinforcement learning, and the AWS DeepRacer League is the world’s first global autonomous racing league. It’s a fun and easy way to get started with machine learning (ML), regardless of […]

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Amazon Personalize improvements reduce model training time by up to 40% and latency for generating recommendations by up to 30%

We’re excited to announce new efficiency improvements for Amazon Personalize. These improvements decrease the time required to train solutions (the machine learning models trained with your data) by up to 40% and reduce the latency for generating real-time recommendations by up to 30%. Amazon Personalize enables you to build applications with the same machine learning […]

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Amazon Rekognition adds support for six new content moderation categories

Amazon Rekognition content moderation is a deep learning-based service that can detect inappropriate, unwanted, or offensive images and videos, making it easier to find and remove such content at scale. Amazon Rekognition provides a detailed taxonomy of moderation categories, such as Explicit Nudity, Suggestive, Violence, and Visually Disturbing. You can now detect six new categories: […]

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Making cycling safer with AWS DeepLens and Amazon SageMaker object detection

According to the 2018 National Highway Traffic Safety Administration (NHTSA) Traffic Safety Facts, in 2018, there were 857 fatal bicycle and motor vehicle crashes and an additional estimated 47,000 cycling injuries in the US . While motorists often accuse cyclists of being the cause of bike-car accidents, the analysis shows that this is not the […]

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