AWS Machine Learning Blog

Category: AWS Lambda

Using container images to run TensorFlow models in AWS Lambda

TensorFlow is an open-source machine learning (ML) library widely used to develop neural networks and ML models. Those models are usually trained on multiple GPU instances to speed up training, resulting in expensive training time and model sizes up to a few gigabytes. After they’re trained, these models are deployed in production to produce inferences. […]

The following is the architecture diagram for integrating online ML inference in a telemedicine contact flow via HAQM Connect.

Applying voice classification in an HAQM Connect telemedicine contact flow

Given the rising demand for fast and effective COVID-19 detection, customers are exploring the usage of respiratory sound data, like coughing, breathing, and counting, to automatically diagnose COVID-19 based on machine learning (ML) models. University of Cambridge researchers built a COVID-19 sound application and demonstrated that a simple binary ML classifier can classify healthy and […]

Using container images to run PyTorch models in AWS Lambda

July 2024: This post was reviewed for accuracy. PyTorch is an open-source machine learning (ML) library widely used to develop neural networks and ML models. Those models are usually trained on multiple GPU instances to speed up training, resulting in expensive training time and model sizes up to a few gigabytes. After they’re trained, these […]

Model serving made easier with Deep Java Library and AWS Lambda

Developing and deploying a deep learning model involves many steps: gathering and cleansing data, designing the model, fine-tuning model parameters, evaluating the results, and going through it again until a desirable result is achieved. Then comes the final step: deploying the model. AWS Lambda is one of the most cost effective service that lets you run code without […]

Intelligently connect to customers using machine learning in the COVID-19 pandemic

The pandemic has changed how people interact, how we receive information, and how we get help. It has shifted much of what used to happen in-person to online. Many of our customers are using machine learning (ML) technology to facilitate that transition, from new remote cloud contact centers, to chatbots, to more personalized engagements online. […]

Build, test, and deploy your HAQM Sagemaker inference models to AWS Lambda

HAQM SageMaker is a fully managed platform that enables developers and data scientists to quickly and easily build, train, and deploy machine learning (ML) models at any scale. When you deploy an ML model, HAQM SageMaker leverages ML hosting instances to host the model and provides an API endpoint to provide inferences. It may also […]

Turning unstructured text into insights with Bewgle powered by AWS

Bewgle is an SAP.iO, Techstars-funded company that uses AWS services to surface insights from user-generated text and audio streams. Bewgle generates insights to help product managers to increase customer satisfaction and engagement with their various products—beauty, electronics, or anything in between.  By listening to the voices of their customers with the help of Bewgle powered […]

Build text analytics solutions with HAQM Comprehend and HAQM Relational Database Service

In this blog post, we will show you how to get started building rich text analytics views from your database, without having to learn anything about machine learning for natural language processing models. We’ll do this by leveraging HAQM Comprehend, paired with HAQM Aurora-MySQL and AWS Lambda.

Build automatic analysis of body language to gauge attention and engagement using HAQM Kinesis Video Streams and HAQM AI Services

August 30, 2023: HAQM Kinesis Data Analytics has been renamed to HAQM Managed Service for Apache Flink. Read the announcement in the AWS News Blog and learn more. This is a guest blog post by Ned T. Sahin, PhD (Brain Power LLC and Harvard University), Runpeng Liu (Brain Power LLC and MIT), Joseph Salisbury, PhD […]

How to Deploy Deep Learning Models with AWS Lambda and Tensorflow

Deep learning has revolutionized how we process and handle real-world data. There are many types of deep learning applications, including applications to organize a user’s photo archive, make book recommendations, detect fraudulent behavior, and perceive the world around an autonomous vehicle. In this post, we’ll show you step-by-step how to use your own custom-trained models […]