Tag: Amazon ML Solutions Lab
How United Airlines built a cost-efficient Optical Character Recognition active learning pipeline | Amazon Web Services
In this post, we discuss how United Airlines, in collaboration with the Amazon Machine Learning Solutions Lab, build an active learning framework on AWS...
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Use the AWS CDK to deploy Amazon SageMaker Studio lifecycle configurations | Amazon Web Services
Amazon SageMaker Studio is the first fully integrated development environment (IDE) for machine learning (ML). Studio provides a single web-based visual interface where you...
Implement a multi-object tracking solution on a custom dataset with Amazon SageMaker | Amazon Web Services
The demand for multi-object tracking (MOT) in video analysis has increased significantly in many industries, such as live sports, manufacturing, and traffic monitoring. For...
How RallyPoint and AWS are personalizing job recommendations to help military veterans and service providers transition back into civilian life using Amazon Personalize
This post was co-written with Dave Gowel, CEO of RallyPoint. In his own words, “RallyPoint is an online social and professional network for veterans,...
Build Streamlit apps in Amazon SageMaker Studio
Developing web interfaces to interact with a machine learning (ML) model is a tedious task. With Streamlit, developing demo applications for your ML solution...
Predicting new and existing product sales in semiconductors using Amazon Forecast
This is a joint post by NXP SEMICONDUCTORS N.V. & AWS Machine Learning Solutions Lab (MLSL) Machine learning (ML) is being used across a...
How Kakao Games automates lifetime value prediction from game data using Amazon SageMaker and AWS Glue
This post is co-written with Suhyoung Kim, General Manager at KakaoGames Data Analytics Lab. Kakao Games is a top video game publisher and developer...
Identifying defense coverage schemes in NFL’s Next Gen Stats
This post is co-written with Jonathan Jung, Mike Band, Michael Chi, and Thompson Bliss at the National Football League. A coverage scheme refers...
Predict football punt and kickoff return yards with fat-tailed distribution using GluonTS
Today, the NFL is continuing their journey to increase the number of statistics provided by the Next Gen Stats Platform to all 32 teams...
Set up Amazon SageMaker Studio with Jupyter Lab 3 using the AWS CDK
Amazon SageMaker Studio is a fully integrated development environment (IDE) for machine learning (ML) partly based on JupyterLab 3. Studio provides a web-based interface to...
Federated Learning on AWS with FedML: Health analytics without sharing sensitive data – Part 1
This blog post is co-written with Chaoyang He and Salman Avestimehr from FedML. Analyzing real-world healthcare and life sciences (HCLS) data poses several practical...
Power recommendations and search using an IMDb knowledge graph – Part 3
This three-part series demonstrates how to use graph neural networks (GNNs) and Amazon Neptune to generate movie recommendations using the IMDb and Box Office...
Power recommendations and search using an IMDb knowledge graph – Part 2
This three-part series demonstrates how to use graph neural networks (GNNs) and Amazon Neptune to generate movie recommendations using the IMDb and Box Office...
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