AWS Machine Learning Blog
Category: Artificial Intelligence
Anomaly detection with Amazon SageMaker Edge Manager using AWS IoT Greengrass V2
Deploying and managing machine learning (ML) models at the edge requires a different set of tools and skillsets as compared to the cloud. This is primarily due to the hardware, software, and networking restrictions at the edge sites. This makes deploying and managing these models more complex. An increasing number of applications, such as industrial […]
How Kustomer utilizes custom Docker images & Amazon SageMaker to build a text classification pipeline
This is a guest post by Kustomer’s Senior Software & Machine Learning Engineer, Ian Lantzy, and AWS team Umesh Kalaspurkar, Prasad Shetty, and Jonathan Greifenberger. In Kustomer’s own words, “Kustomer is the omnichannel SaaS CRM platform reimagining enterprise customer service to deliver standout experiences. Built with intelligent automation, we scale to meet the needs of […]
Build, train, and deploy Amazon Lookout for Equipment models using the Python Toolbox
Predictive maintenance can be an effective way to prevent industrial machinery failures and expensive downtime by proactively monitoring the condition of your equipment, so you can be alerted to any anomalies before equipment failures occur. Installing sensors and the necessary infrastructure for data connectivity, storage, analytics, and alerting are the foundational elements for enabling predictive […]
Choose the best data source for your Amazon SageMaker training job
Amazon SageMaker is a managed service that makes it easy to build, train, and deploy machine learning (ML) models. Data scientists use SageMaker training jobs to easily train ML models; you don’t have to worry about managing compute resources, and you pay only for the actual training time. Data ingestion is an integral part of […]
How InpharmD uses Amazon Kendra and Amazon Lex to drive evidence-based patient care
The intersection of DI and AI: Drug information refers to the discovery, use, and management of healthcare and medical information. Healthcare providers have many challenges associated with drug information discovery, such as intensive time involvement, lack of accessibility, and accuracy of reliable data. The average clinical query requires a literature search that takes an average of 18.5 hours. In addition, drug information often lies in disparate information silos, behind pay walls and design walls, and quickly becomes stale.
Control formality in machine translated text using Amazon Translate
Amazon Translate is a neural machine translation service that delivers fast, high-quality, affordable, and customizable language translation. Amazon Translate now supports formality customization. This feature allows you to customize the level of formality in your translation output. At the time of writing, the formality customization feature is available for six target languages: French, German, Hindi, Italian, […]
Bongo Learn provides real-time feedback to improve learning outcomes with Amazon Transcribe
Real-time feedback helps drive learning. This is especially important for designing presentations, learning new languages, and strengthening other essential skills that are critical to succeed in today’s workplace. However, many students and lifelong learners lack access to effective face-to-face instruction to hone these skills. In addition, with the rapid adoption of remote learning, educators are […]
Prepare time series data with Amazon SageMaker Data Wrangler
Time series data is widely present in our lives. Stock prices, house prices, weather information, and sales data captured over time are just a few examples. As businesses increasingly look for new ways to gain meaningful insights from time-series data, the ability to visualize data and apply desired transformations are fundamental steps. However, time-series data […]
Automate a shared bikes and scooters classification model with Amazon SageMaker Autopilot
February 9, 2024: Amazon Kinesis Data Firehose has been renamed to Amazon Data Firehose. Read the AWS What’s New post to learn more. Amazon SageMaker Autopilot makes it possible for organizations to quickly build and deploy an end-to-end machine learning (ML) model and inference pipeline with just a few lines of code or even without […]
Apply profanity masking in Amazon Translate
Amazon Translate is a neural machine translation service that delivers fast, high-quality, affordable, and customizable language translation. This post shows how you can mask profane words and phrases with a grawlix string (“?$#@$”). Amazon Translate typically chooses clean words for your translation output. But in some situations, you want to prevent words that are commonly […]