Synopsis
"MLflow Unleashed: Real-World MLOps Workflows" is the definitive guide for machine learning engineers, data scientists, and technical leaders seeking to master the orchestration of robust, end-to-end MLOps solutions with MLflow at their core. The book opens with a forward-thinking exploration of modern MLOps challenges, thoughtfully contrasting them with traditional DevOps, and meticulously introduces MLflow’s architecture—from experiment tracking and model management to registry and plugin extensibility. Readers are empowered with practical decision frameworks, advanced integration strategies for hybrid and cloud environments, and best practices for embedding MLflow seamlessly within an enterprise's data and machine learning ecosystem.
Through detailed chapters on architecting resilient MLflow platforms, securing deployments, and implementing operational excellence, the book illuminates the path to scalable, production-grade workflows. It dives deep into automating experiment management, ensuring governance and compliance, and scaling collaboration across teams. Special attention is given to advanced reproducibility, lineage, and automation techniques using CI/CD, Kubernetes-native patterns, GitOps workflows, and infrastructure-as-code, ensuring repeatability and auditability in even the most complex environments. Readers will also uncover actionable approaches for model deployment, monitoring, and lifecycle management—including batch, real-time, and edge serving, as well as sophisticated rollback and canary release strategies.
"MLflow Unleashed" culminates in expert guidance for extending MLflow to meet diverse organizational needs, from custom plugins and horizontal scaling to cost optimization and responsible AI practices. The book provides comprehensive insights on monitoring, observability, bias mitigation, and regulatory compliance, equipping practitioners to build accountable and future-proof AI systems. Both a practical handbook and a strategic reference, this work is essential for anyone committed to scaling machine learning operations with rigor, efficiency, and innovation in the real world.
Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.
Résultats de recherche pour MLflow Unleashed: Real-World MLOps Workflows
Image d'archives
MLflow Unleashed: Real-World MLOps Workflows
impression à la demandeVendeur : California Books, Miami, FL, Etats-Unis
Évaluation du vendeur 4 sur 5 étoiles
Etat : New. Print on Demand. N° de réf. du vendeur I-9798296681942
Acheter neuf
EUR 37,90
Livraison gratuite
Expédition nationale : Etats-Unis
Expédition nationale : Etats-Unis
Quantité disponible : Plus de 20 disponibles
Image d'archives
MLflow Unleashed
Vendeur : PBShop.store UK, Fairford, GLOS, Royaume-Uni
Évaluation du vendeur 5 sur 5 étoiles
PAP. Etat : New. New Book. Shipped from UK. Established seller since 2000. N° de réf. du vendeur L2-9798296681942
Acheter neuf
EUR 38,51
Expédition à EUR 4,88
Expédition depuis Royaume-Uni vers Etats-Unis
Expédition depuis Royaume-Uni vers Etats-Unis
Quantité disponible : Plus de 20 disponibles
Image d'archives
MLflow Unleashed (Paperback)
impression à la demandeVendeur : CitiRetail, Stevenage, Royaume-Uni
Évaluation du vendeur 5 sur 5 étoiles
Paperback. Etat : new. Paperback. "MLflow Unleashed: Real-World MLOps Workflows" is the definitive guide for machine learning engineers, data scientists, and technical leaders seeking to master the orchestration of robust, end-to-end MLOps solutions with MLflow at their core. The book opens with a forward-thinking exploration of modern MLOps challenges, thoughtfully contrasting them with traditional DevOps, and meticulously introduces MLflow's architecture-from experiment tracking and model management to registry and plugin extensibility. Readers are empowered with practical decision frameworks, advanced integration strategies for hybrid and cloud environments, and best practices for embedding MLflow seamlessly within an enterprise's data and machine learning ecosystem. Through detailed chapters on architecting resilient MLflow platforms, securing deployments, and implementing operational excellence, the book illuminates the path to scalable, production-grade workflows. It dives deep into automating experiment management, ensuring governance and compliance, and scaling collaboration across teams. Special attention is given to advanced reproducibility, lineage, and automation techniques using CI/CD, Kubernetes-native patterns, GitOps workflows, and infrastructure-as-code, ensuring repeatability and auditability in even the most complex environments. Readers will also uncover actionable approaches for model deployment, monitoring, and lifecycle management-including batch, real-time, and edge serving, as well as sophisticated rollback and canary release strategies. "MLflow Unleashed" culminates in expert guidance for extending MLflow to meet diverse organizational needs, from custom plugins and horizontal scaling to cost optimization and responsible AI practices. The book provides comprehensive insights on monitoring, observability, bias mitigation, and regulatory compliance, equipping practitioners to build accountable and future-proof AI systems. Both a practical handbook and a strategic reference, this work is essential for anyone committed to scaling machine learning operations with rigor, efficiency, and innovation in the real world. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. N° de réf. du vendeur 9798296681942
Acheter neuf
EUR 42,91
Expédition à EUR 43,44
Expédition depuis Royaume-Uni vers Etats-Unis
Expédition depuis Royaume-Uni vers Etats-Unis
Quantité disponible : 1 disponible(s)