AWS Machine Learning Blog
Perform medical transcription analysis in real-time with AWS AI services and Twilio Media Streams
Medical providers often need to analyze and dictate patient phone conversations, doctors’ notes, clinical trial reports, and patient health records. By automating transcription, providers can quickly and accurately provide patients with medical conditions, medication, dosage, strength, and frequency. Generic artificial intelligence-based transcription models can be used to transcribe voice to text. However, medical voice data […]
Amazon Forecast now provides estimated run time for forecast creation jobs, enabling you to manage your time efficiently
Amazon Forecast now displays the estimated time it takes to complete an in-progress workflow for importing your data, training the predictor, and generating the forecast. You can now manage your time more efficiently and better plan for your next workflow around the estimated time remaining for your in-progress workflow. Forecast uses machine learning (ML) to […]
Build an event-based tracking solution using Amazon Lookout for Vision
Amazon Lookout for Vision is a machine learning (ML) service that spots defects and anomalies in visual representations using computer vision (CV). With Amazon Lookout for Vision, manufacturing companies can increase quality and reduce operational costs by quickly identifying differences in images of objects at scale. Many enterprise customers want to identify missing components in […]
Quality Assessment for SageMaker Ground Truth Video Object Tracking Annotations using Statistical Analysis
Data quality is an important topic for virtually all teams and systems deriving insights from data, especially teams and systems using machine learning (ML) models. Supervised ML is the task of learning a function that maps an input to an output based on examples of input-output pairs. For a supervised ML algorithm to effectively learn […]
It’s here! Join us for Amazon SageMaker Month, 30 days of content, discussion, and news
Want to accelerate machine learning (ML) innovation in your organization? Join us for 30 days of new Amazon SageMaker content designed to help you build, train, and deploy ML models faster. On April 20, we’re kicking off 30 days of hands-on workshops, Twitch sessions, Slack chats, and partner perspectives. Our goal is to connect you […]
Enforce VPC rules for Amazon Comprehend jobs and CMK encryption for custom models
You can now control the Amazon Virtual Private Cloud (Amazon VPC) and encryption settings for your Amazon Comprehend APIs using AWS Identity and Access Management (IAM) condition keys, and encrypt your Amazon Comprehend custom models using customer managed keys (CMK) via AWS Key Management Service (AWS KMS). IAM condition keys enable you to further refine […]
AWS launches free digital training courses to empower business leaders with ML knowledge
Today, we’re pleased to launch Machine Learning Essentials for Business and Technical Decision Makers—a series of three free, on-demand, digital-training courses from AWS Training and Certification. These courses are intended to empower business leaders and technical decision makers with the foundational knowledge needed to begin shaping a machine learning (ML) strategy for their organization, even […]
Estimating 3D pose for athlete tracking using 2D videos and Amazon SageMaker Studio
In preparation for the upcoming Olympic Games, Intel®, an American multinational corporation and one of the world’s largest technology companies, developed a concept around 3D Athlete Tracking (3DAT). 3DAT is a machine learning (ML) solution to create real-time digital models of athletes in competition in order to increase fan engagement during broadcasts. Intel was looking […]
Implement checkpointing with TensorFlow for Amazon SageMaker Managed Spot Training
Customers often ask us how can they lower their costs when conducting deep learning training on AWS. Training deep learning models with libraries such as TensorFlow, PyTorch, and Apache MXNet usually requires access to GPU instances, which are AWS instances types that provide access to NVIDIA GPUs with thousands of compute cores. GPU instance types […]
HawkEye 360 uses Amazon SageMaker Autopilot to streamline machine learning model development for maritime vessel risk assessment
This post is cowritten by Ian Avilez and Tim Pavlick from HawkEye 360. HawkEye 360 is a commercial radio frequency (RF) satellite constellation data analytics provider. Our signals of interest include very high frequency (VHF) push-to-talk radios, maritime radar systems, AIS beacons, satellite mobile comms, and more. Our Mission Space offering, released in February 2021, […]