Enable Scala & Spark in SageMaker Studio with Almond Kernel
Learn to integrate Scala into Amazon SageMaker Studio using the Almond kernel and Coursier. Enhance Spark-based workflows and leverage Scala’s power for ML development.
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Supercharge SageMaker with Comet: Enterprise ML Experiment Management
Boost your ML workflow with Comet and SageMaker AI! This integration provides seamless experiment management, model tracking, and collaboration for enterprise-scale machine learning projects, ensuring compliance and efficiency.
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SageMaker HyperPod: Topology-Aware AI Workload Scheduling
Optimize your AI workloads with Amazon SageMaker HyperPod’s new topology-aware scheduling. Reduce network latency and improve training efficiency using EC2 instance topology information for enhanced resource allocation and task prioritization.
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AWS CDK for SageMaker Ground Truth Private Workforce
Automate SageMaker Ground Truth private workforce creation with AWS CDK. This solution handles Cognito integration, callback URLs, and domain management for secure, scalable data labeling.
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SageMaker HyperPod: Fine-Grained Quota Control for Optimized Cluster Use
Maximize Amazon SageMaker HyperPod cluster utilization with fine-grained quota allocation. Control GPU, vCPU, and memory resources across teams, optimizing resource distribution and cost efficiency. Learn how to use the AWS Management Console or CLI.
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SageMaker HyperPod Auto Scaling with Karpenter: Cost-Optimized Inference
Amazon SageMaker HyperPod now offers managed auto-scaling with Karpenter, optimizing resource utilization and costs for large-scale ML workloads. Enable just-in-time provisioning, scale to zero, and integrate with KEDA for event-driven scaling.
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Customize Amazon Nova with SageMaker: Direct Preference Optimization
Learn how to customize Amazon Nova foundation models using SageMaker’s Direct Preference Optimization for improved performance and alignment with your business needs.
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Fine-Tuning LLMs on Amazon SageMaker: A Guide
Master LLM fine-tuning with Amazon SageMaker. Explore SFT, PEFT methods, optimization techniques, and more. Democratize AI development with AWS.
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Amazon SageMaker’s MLflow 3.0: Revolutionizing Generative AI
Accelerate generative AI development with Amazon SageMaker’s fully managed MLflow 3.0. Streamline experimentation, improve observability, and reduce time-to-market.
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Amazon SageMaker HyperPod: Faster Generative AI Model Deployments
Accelerate generative AI with Amazon SageMaker HyperPod’s new model deployment features. Deploy from JumpStart, S3, or FSx; leverage dynamic scaling & comprehensive observability. Streamline your AI workflow today!
