Mastering Machine Learning on Kubernetes
Advanced Strategies for Scalable, Efficient, and Secure ML Systems
Created by ChrisElevate your Machine Learning infrastructure to new heights with Kubernetes. This comprehensive guide equips you with cutting-edge techniques to architect, deploy, and manage sophisticated ML systems at scale. You'll dive deep into advanced topics such as distributed training, GPU optimization, and MLOps best practices, all within the Kubernetes ecosystem. Discover how to leverage custom resources, implement robust CI/CD pipelines, and optimize resource utilization for your ML workloads. You'll learn to seamlessly integrate tools like Kubeflow, Istio, and Prometheus to create a powerful, flexible ML platform. With hands-on examples and real-world scenarios, you'll master the art of building resilient, high-performance ML systems that can handle the most demanding computational challenges. Whether you're fine-tuning model serving strategies, implementing advanced security measures, or orchestrating complex distributed learning tasks, this book provides the expert-level insights you need. By the end, you'll possess the skills to design and maintain state-of-the-art ML infrastructure that scales effortlessly with your organization's needs.
Est. Length
300 pages (16 chapters)
Language
English
Publication date
Mar 23, 2025
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