Accelerating AI/ML development at BMW Group with Amazon SageMaker Studio | Amazon Web Services Source Cluster: AWS Machine Learning Source Node: 2397648Time Stamp: Nov 24, 2023
Implement data warehousing solution using dbt on Amazon Redshift | Amazon Web Services Source Cluster: AWS Big Data Source Node: 2388625Time Stamp: Nov 17, 2023
Philips accelerates development of AI-enabled healthcare solutions with an MLOps platform built on Amazon SageMaker | Amazon Web Services Source Cluster: AWS Machine Learning Source Node: 2385144Time Stamp: Nov 16, 2023
BMW Cloud Efficiency Analytics powered by Amazon QuickSight and Amazon Athena | Amazon Web Services Source Cluster: AWS Big Data Source Node: 2391561Time Stamp: Nov 15, 2023
Implement real-time personalized recommendations using Amazon Personalize | Amazon Web Services Source Cluster: AWS Machine Learning Source Node: 2381252Time Stamp: Nov 13, 2023
MAS Public Cloud Guidelines: A Deep Dive into its Impact on Cloud Security – Fintech Singapore Source Cluster: Fintechnews Singapore Source Node: 2376250Time Stamp: Nov 9, 2023
Promote pipelines in a multi-environment setup using Amazon SageMaker Model Registry, HashiCorp Terraform, GitHub, and Jenkins CI/CD | Amazon Web Services Source Cluster: AWS Machine Learning Source Node: 2375913Time Stamp: Nov 9, 2023
Bundesliga Match Facts Shot Speed – Who fires the hardest shots in the Bundesliga? | Amazon Web Services Source Cluster: AWS Machine Learning Source Node: 2364810Time Stamp: Nov 3, 2023
Optimize pet profiles for Purina’s Petfinder application using Amazon Rekognition Custom Labels and AWS Step Functions | Amazon Web Services Source Cluster: AWS Machine Learning Source Node: 2334567Time Stamp: Oct 18, 2023
Robust time series forecasting with MLOps on Amazon SageMaker | Amazon Web Services Source Cluster: AWS Machine Learning Source Node: 2299622Time Stamp: Sep 28, 2023
Designing resilient cities at Arup using Amazon SageMaker geospatial capabilities | Amazon Web Services Source Cluster: AWS Machine Learning Source Node: 2278565Time Stamp: Sep 18, 2023
Build a classification pipeline with Amazon Comprehend custom classification (Part I) | Amazon Web Services Source Cluster: AWS Machine Learning Source Node: 2270643Time Stamp: Sep 14, 2023
Simplify operational data processing in data lakes using AWS Glue and Apache Hudi | Amazon Web Services Source Cluster: AWS Big Data Source Node: 2269508Time Stamp: Sep 13, 2023
Amazon SageMaker Domain in VPC only mode to support SageMaker Studio with auto shutdown Lifecycle Configuration and SageMaker Canvas with Terraform | Amazon Web Services Source Cluster: AWS Machine Learning Source Node: 2265833Time Stamp: Sep 11, 2023
MLOps for batch inference with model monitoring and retraining using Amazon SageMaker, HashiCorp Terraform, and GitLab CI/CD | Amazon Web Services Source Cluster: AWS Machine Learning Source Node: 2243290Time Stamp: Aug 29, 2023
Automate the archive and purge data process for Amazon RDS for PostgreSQL using pg_partman, Amazon S3, and AWS Glue | Amazon Web Services Source Cluster: AWS Big Data Source Node: 2228862Time Stamp: Aug 22, 2023
Implement a serverless CDC process with Apache Iceberg using Amazon DynamoDB and Amazon Athena | Amazon Web Services Source Cluster: AWS Big Data Source Node: 2217247Time Stamp: Aug 16, 2023
Monitor data pipelines in a serverless data lake | Amazon Web Services Source Cluster: AWS Big Data Source Node: 2204193Time Stamp: Aug 9, 2023
Generate creative advertising using generative AI deployed on Amazon SageMaker | Amazon Web Services Source Cluster: AWS Machine Learning Source Node: 2203642Time Stamp: Aug 9, 2023
AWS performs fine-tuning on a Large Language Model (LLM) to classify toxic speech for a large gaming company | Amazon Web Services Source Cluster: AWS Machine Learning Source Node: 2200880Time Stamp: Aug 7, 2023