AWS Machine Learning Blog

In the past decade, deep learning has advanced many different areas, such as computer vision and natural language processing. State-of-the-art models now achieve near-human performance in tasks such as image classification. Deep neural networks can achieve this because they consist of millions of parameters that you train on large training datasets. For instance, the BERT […]

When running deep learning models in production, balancing infrastructure cost versus model latency is always an important consideration. At re:Invent 2018, AWS introduced Amazon SageMaker Neo and Amazon Elastic Inference, two services that can make models more efficient for deep learning. In most deep learning applications, making predictions using a trained model—a process called inference—can […]

This post is co-written by Arte Merritt, co-founder and CEO of Dashbot. In their own words, “Dashbot is an analytics platform for chatbots and voice skills that enables enterprises to increase engagement, satisfaction, and conversions through actionable insights and tools.” After you have deployed a bot, it is critical to analyze bot interactions, learn from […]

Starting Tuesday, March 24, 2020, NVIDIA GTC Digital is offering courses for you to learn AWS best practices to accomplish your ML goals faster and more easily. Registration is free, so register now. The following sessions are available from AWS: S22492: Train BERT in One Hour Using Massive Cloud Scale Distributed Deep Learning Learn how […]

In this blog post, we show you how to build a prototype trash sorter using AWS DeepLens, the AWS deep learning-enabled video camera designed for developers to learn machine learning in a fun, hands-on way. This prototype trash sorter project teaches you how to train image classification models with custom data. Image classification is a […]

Amazon Forecast is a fully managed service that uses machine learning (ML) to generate highly accurate forecasts, without requiring any prior ML experience. Forecast is applicable in a wide variety of use cases, including energy demand forecasting, estimating product demand, workforce planning, and computing cloud infrastructure usage. With Forecast, there are no servers to provision […]

Amazon CodeGuru (Preview) analyzes your application’s performance characteristics and provides automatic recommendations on how to improve it. Amazon CodeGuru Profiler provides interactive visualizations to show you where your application spends its time. These flame graphs are a powerful tool to help you troubleshoot which code methods are causing delays or using too much CPU. This […]

With an increasing number of digital text documents shared across the world for both business and personal reasons, the need for translation capabilities becomes even more critical. There are multiple tools available online that enable people to copy/paste text and get the translated equivalent in the language of their choice. While this is a great […]

This is a guest post by Ron Jaworski, co-founder and CEO of Trinity Audio. In their own words, “Trinity Audio is an audio content solution platform that caters to publishers and content creators of all types and sizes worldwide, and helps them join the ongoing audio revolution by turning readers into listeners, creating the experience […]

Today, we are excited to announce that you can now use Amazon Elastic Inference to accelerate inference and reduce inference costs for PyTorch models in both Amazon SageMaker and Amazon EC2. PyTorch is a popular deep learning framework that uses dynamic computational graphs. This allows you to easily develop deep learning models with imperative and […]