Meta launches its Llama 3 open-source LLM on Amazon AWS – Tech Startups Source Cluster: TechStartups Source Node: 2551472Time Stamp: Apr 18, 2024
Meta Llama 3 models are now available in Amazon SageMaker JumpStart | Amazon Web Services Source Cluster: AWS Machine Learning Source Node: 2553444Time Stamp: Apr 18, 2024
Automate Amazon SageMaker Pipelines DAG creation | Amazon Web Services Source Cluster: AWS Machine Learning Source Node: 2502317Time Stamp: Feb 29, 2024
How Booking.com modernized its ML experimentation framework with Amazon SageMaker | Amazon Web Services Source Cluster: AWS Machine Learning Source Node: 2478329Time Stamp: Feb 12, 2024
Build an end-to-end MLOps pipeline using Amazon SageMaker Pipelines, GitHub, and GitHub Actions | Amazon Web Services Source Cluster: AWS Machine Learning Source Node: 2419445Time Stamp: Dec 13, 2023
Operationalize LLM Evaluation at Scale using Amazon SageMaker Clarify and MLOps services | Amazon Web Services Source Cluster: AWS Machine Learning Source Node: 2404648Time Stamp: Nov 29, 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
Governing the ML lifecycle at scale, Part 1: A framework for architecting ML workloads using Amazon SageMaker | Amazon Web Services Source Cluster: AWS Machine Learning Source Node: 2339744Time Stamp: Oct 20, 2023
Automatically redact PII for machine learning using Amazon SageMaker Data Wrangler | Amazon Web Services Source Cluster: AWS Machine Learning Source Node: 2336276Time Stamp: Oct 19, 2023
Best Practices for Building ETLs for ML – KDnuggets Source Cluster: KDnuggets Source Node: 2327608Time Stamp: Oct 12, 2023
Build an end-to-end MLOps pipeline for visual quality inspection at the edge – Part 2 | Amazon Web Services Source Cluster: AWS Machine Learning Source Node: 2304247Time Stamp: Oct 2, 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
Orchestrate Ray-based machine learning workflows using Amazon SageMaker | Amazon Web Services Source Cluster: AWS Machine Learning Source Node: 2278563Time Stamp: Sep 18, 2023
Accelerate client success management through email classification with Hugging Face on Amazon SageMaker | Amazon Web Services Source Cluster: AWS Machine Learning Source Node: 2267433Time Stamp: Sep 12, 2023
Best practices and design patterns for building machine learning workflows with Amazon SageMaker Pipelines | Amazon Web Services Source Cluster: AWS Machine Learning Source Node: 2261541Time Stamp: Sep 7, 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
Build ML features at scale with Amazon SageMaker Feature Store using data from Amazon Redshift | Amazon Web Services Source Cluster: AWS Machine Learning Source Node: 2218235Time Stamp: Aug 17, 2023
Unlocking efficiency: Harnessing the power of Selective Execution in Amazon SageMaker Pipelines | Amazon Web Services Source Cluster: AWS Machine Learning Source Node: 2218237Time Stamp: Aug 16, 2023
Optimize data preparation with new features in AWS SageMaker Data Wrangler | Amazon Web Services Source Cluster: AWS Machine Learning Source Node: 2196646Time Stamp: Aug 4, 2023
Scale training and inference of thousands of ML models with Amazon SageMaker | Amazon Web Services Source Cluster: AWS Machine Learning Source Node: 2195571Time Stamp: Aug 3, 2023