AWS Machine Learning Blog
Category: Learning Levels
Announcing the updated Microsoft SharePoint connector (V2.0) for Amazon Kendra
Amazon Kendra is a highly accurate and simple-to-use intelligent search service powered by machine learning (ML). Amazon Kendra offers a suite of data source connectors to simplify the process of ingesting and indexing your content, wherever it resides. Valuable data in organizations is stored in both structured and unstructured repositories. Amazon Kendra can pull together […]
Prepare training and validation dataset for facies classification using a Snowflake OAuth connection and Amazon SageMaker Canvas
February 2024: This post was reviewed and updated for accuracy. This post is co-written with Thatcher Thornberry from bpx energy. Facies classification is the process of segmenting lithologic formations from geologic data at the wellbore location. During drilling, wireline logs are obtained, which have depth-dependent geologic information. Geologists are deployed to analyze this log data […]
GPT-NeoXT-Chat-Base-20B foundation model for chatbot applications is now available on Amazon SageMaker
Today we are excited to announce that Together Computer’s GPT-NeoXT-Chat-Base-20B language foundation model is available for customers using Amazon SageMaker JumpStart. GPT-NeoXT-Chat-Base-20B is an open-source model to build conversational bots. You can easily try out this model and use it with JumpStart. JumpStart is the machine learning (ML) hub of Amazon SageMaker that provides access […]
Introducing Amazon Textract Bulk Document Uploader for enhanced evaluation and analysis
Amazon Textract is a machine learning (ML) service that automatically extracts text, handwriting, and data from any document or image. To make it simpler to evaluate the capabilities of Amazon Textract, we have launched a new Bulk Document Uploader feature on the Amazon Textract console that enables you to quickly process your own set of […]
AI-powered code suggestions and security scans in Amazon SageMaker notebooks using Amazon CodeWhisperer and Amazon CodeGuru
Amazon SageMaker comes with two options to spin up fully managed notebooks for exploring data and building machine learning (ML) models. The first option is fast start, collaborative notebooks accessible within Amazon SageMaker Studio—a fully integrated development environment (IDE) for machine learning. You can quickly launch notebooks in Studio, easily dial up or down the […]
Unlock insights from your Amazon S3 data with intelligent search
Amazon Kendra is an intelligent search service powered by machine learning (ML). Amazon Kendra reimagines enterprise search for your websites and applications so your employees and customers can easily find the content they’re looking for, even when it’s scattered across multiple locations and content repositories within your organization. Keywords or natural language questions can be […]
Operationalize ML models built in Amazon SageMaker Canvas to production using the Amazon SageMaker Model Registry
You can now register machine learning (ML) models built in Amazon SageMaker Canvas with a single click to the Amazon SageMaker Model Registry, enabling you to operationalize ML models in production. Canvas is a visual interface that enables business analysts to generate accurate ML predictions on their own—without requiring any ML experience or having to […]
Amazon SageMaker with TensorBoard: An overview of a hosted TensorBoard experience
Today, data scientists who are training deep learning models need to identify and remediate model training issues to meet accuracy targets for production deployment, and require a way to utilize standard tools for debugging model training. Among the data scientist community, TensorBoard is a popular toolkit that allows data scientists to visualize and analyze various […]
How Sleepme uses Amazon SageMaker for automated temperature control to maximize sleep quality in real time
This is a guest post co-written with Trey Robinson, CTO at Sleepme Inc. Sleepme is an industry leader in sleep temperature management and monitoring products, including an Internet of Things (IoT) enabled sleep tracking sensor suite equipped with heart rate, respiration rate, bed and ambient temperature, humidity, and pressure sensors. Sleepme offers a smart mattress […]
Publish predictive dashboards in Amazon QuickSight using ML predictions from Amazon SageMaker Canvas
April 2024: This post was reviewed and updated for accuracy. Understanding business trends, customer behavior, sales revenue, increase in demand, and buyer propensity all start with data. Exploring, analyzing, interpreting, and finding trends in data is essential for businesses to achieve successful outcomes. Business analysts play a pivotal role in facilitating data-driven business decisions through […]