Artificial Intelligence
Category: Amazon SageMaker
Protecting people from hazardous areas through virtual boundaries with Computer Vision
April 2023 Update: Starting January 31, 2024, you will no longer be able to access AWS DeepLens through the AWS management console, manage DeepLens devices, or access any projects you have created. To learn more, refer to these frequently asked questions about AWS DeepLens end of life. As companies welcome more autonomous robots and other heavy […]
Enable cross-account access for Amazon SageMaker Data Wrangler using AWS Lake Formation
Amazon SageMaker Data Wrangler is the fastest and easiest way for data scientists to prepare data for machine learning (ML) applications. With Data Wrangler, you can simplify the process of feature engineering and complete each step of the data preparation workflow, including data selection, cleansing, exploration, and visualization through a single visual interface. Data Wrangler […]
Win a digital car and personalize your racer profile on the AWS DeepRacer console
AWS DeepRacer is the fastest way to get rolling with machine learning, giving developers the chance to learn ML hands-on with a 1/18th scale autonomous car, 3D virtual racing simulator, and the world’s largest global autonomous car racing league. With the 2021 AWS DeepRacer League Virtual Circuit now underway, developers have five times more opportunities […]
Object detection with Detectron2 on Amazon SageMaker
Deep learning is at the forefront of most machine learning (ML) implementations across a broad set of business verticals. Driven by the highly flexible nature of neural networks, the boundary of what is possible has been pushed to a point where neural networks can outperform humans in a variety of tasks, such as object detection […]
Join AWS at NVIDIA GTC 21, April 12–16
Starting Monday, April 12, 2021, the NVIDIA GPU Technology Conference (GTC) is offering online sessions for you to learn AWS best practices to accomplish your machine learning (ML), virtual workstations, high performance computing (HPC), and Internet of Things (IoT) goals faster and more easily. Amazon Elastic Compute Cloud (Amazon EC2) instances powered by NVIDIA GPUs […]
Build a CI/CD pipeline for deploying custom machine learning models using AWS services
Amazon SageMaker is a fully managed service that provides every developer and data scientist with the ability to build, train, and deploy machine learning (ML) models quickly. SageMaker removes the heavy lifting from each step of the ML process to make it easier to develop high-quality ML artifacts. AWS Serverless Application Model (AWS SAM) is […]
Rust detection using machine learning on AWS
Visual inspection of industrial environments is a common requirement across heavy industries, such as transportation, construction, and shipbuilding, and typically requires qualified experts to perform the inspection. Inspection locations can often be remote or in adverse environments that put humans at risk, such as bridges, skyscrapers, and offshore oil rigs. Many of these industries deal […]
Aerobotics improves training speed by 24 times per sample with Amazon SageMaker and TensorFlow
Editor’s note: This is a guest post written by Michael Malahe, Head of Data at Aerobotics, a South African startup that builds AI-driven tools for agriculture. Aerobotics is an agri-tech company operating in 18 countries around the world, based out of Cape Town, South Africa. Our mission is to provide intelligent tools to feed the […]
Enable feature reuse across accounts and teams using Amazon SageMaker Feature Store
October 2023: This post was reviewed and updated for accuracy. Amazon SageMaker Feature Store is a new capability of Amazon SageMaker that helps data scientists and machine learning (ML) engineers securely store, discover, and share curated data used in training and prediction workflows. As organizations build data-driven applications using ML, they’re constantly assembling and moving […]
AWS and Hugging Face collaborate to simplify and accelerate adoption of Natural Language Processing models
Just like computer vision a few years ago, the decade-old field of natural language processing (NLP) is experiencing a fascinating renaissance. Not a month goes by without a new breakthrough! Indeed, thanks to the scalability and cost-efficiency of cloud-based infrastructure, researchers are finally able to train complex deep learning models on very large text datasets, […]