The Challenges of Managing Kubernetes-Based Machine Learning Infrastructure
Explore challenges in managing Kubernetes-based ML infrastructure with experts from Bloomberg, Seldon, and Spotify. Learn about tools, use cases, and solutions for on-prem and cloud environments.
How Bloomberg Uses AI to Speed Up Over-the-Counter Trading
Explore how Bloomberg leverages AI and Kubernetes to enhance over-the-counter trading efficiency, focusing on detecting offers in group chats and streamlining negotiations for traders.
Machine Learning Using Various GPU Technologies with Kubeflow
Explore efficient distributed learning in Kubeflow using Multi-Instance GPU and GPUDirect RDMA technologies to maximize GPU utilization and improve performance in machine learning workflows.
Hardening Kubeflow Security for Enterprise Environments
Learn about Kubeflow security vulnerabilities, best practices, and improvements for enterprise environments. Gain insights on addressing unauthorized access, user impersonation, and data protection in MLOps platforms.
Making the Most Out of Hardware Accelerators in Kubernetes Clusters
Optimize GPU and TPU usage in Kubernetes clusters for MLOps. Learn efficient hardware accelerator management, scaling, and time-sharing techniques to enhance machine learning workloads.
Building on-Premises MLOps for ISS Columbus Ground Operations
Explore the development of an on-premises MLOps platform for ISS Columbus operations, covering anomaly detection, root cause analysis, and automated deployment using GitLab, microk8s, and Kubeflow.
GitOps for Machine Learning Pipelines
Explore GitOps for ML pipelines using Kubeflow on Kubernetes. Learn to leverage GitOps for training, inference, monitoring, and testing in ML lifecycles, with a demo on deploying Kubeflow components via Argo CD.
Machine Learning with Kubernetes
Explore MLOps with Kubernetes: Learn to build scalable ML pipelines using Kubeflow, optimize cluster design, and leverage Istio for enhanced observability and security in production environments.
Categorizing Docker Hub's Public Images - End-to-End Machine Learning Pipeline with Docker Enterprise
Discover how Docker Enterprise and Kubeflow enable rapid development of production-ready machine learning pipelines for classifying container images, enhancing Docker Hub's discovery capabilities.
MLOps Automation with Git Based CI-CD for ML
Explore MLOps automation using Git-based CI/CD for ML, covering challenges, collaboration, and streamlined deployment with cloud-native tools and Kubernetes.
Constructing Kubeflow Super Nodes with Karpenter
Learn how Karpenter optimizes AI/ML platforms on Kubernetes by automatically selecting and launching ideal compute resources for Kubeflow Notebooks and Pipelines, enhancing efficiency and scalability.
Scaling ML Pipelines on Kubernetes Using Tekton - Overcoming Complexity
Explore scaling ML pipelines on Kubernetes with Tekton, addressing limitations and enhancing efficiency through custom tasks and integration with KubeFlow for improved scalability in production environments.
Training AI to Code Using Project CodeNet - Largest Code Dataset
Explore Project CodeNet's vast code dataset and learn to leverage it for AI-driven code classification, complexity analysis, and language translation using MLX and Kubernetes.
Hyperparameter Tuning Using Kubeflow
Explore automated machine learning with Katib, a Kubernetes-native platform for hyperparameter tuning and neural architecture search, enhancing model performance efficiently.
Introduction to KubeFlow: Using and Use Cases
Explore KubeFlow for machine learning on Kubernetes, covering components, use cases, and a practical recommender system example with collaborative filtering and TensorFlow.
Manage Multi-tenant ML Workloads Using Istio
Explore Istio integration for multi-tenant ML pipelines on Kubernetes, focusing on workload isolation, access control, and API management. Learn from a Kubeflow case study and live demo.
Defending Against Adversarial Model Attacks Using Kubeflow
Learn to protect AI models from adversarial attacks using Kubeflow. Explore threats, defenses, and practical implementations in this comprehensive presentation by IBM experts.
Securing ML Workloads with Kubeflow and MLOps - Pwned By Statistics
Learn to secure machine learning workloads using Kubeflow and MLOps. Explore techniques like model extraction, hidden data attacks, and leakage detection to protect your ML pipelines and models.
GenOps: Building an MLOps Platform to Support GenAI Workloads with Open-Source and Kubeflow
Explore building an end-to-end MLOps platform on GKE using open-source tools like Kubeflow to support Generative AI models, with practical tips and a demo for leveraging these technologies.
Training and Optimisation of Large Transformer Models - An ATLAS and CERN Use Case
Explore CERN's implementation of transformer models for Jet Flavour Tagging, utilizing Kubeflow for machine learning and Katib for hyperparameter optimization in large-scale particle physics data analysis.
Efficient Integration of Kubeflow Tools - ISS Data Case Study on Anomaly Detection
Explore Kubeflow's integrated tools for ML workflows through an ISS anomaly detection case study, showcasing Dask, Katib, PyTorch Operator, and KServe in a unified KFP pipeline.