Name: Essential Kubeflow: Engineering ML Workflows on Kubernetes (en Inglés)
SKU: 66883692
Price: 206.05 USD
Availability: InStock
Author: Josyula, Prashanth; Arora, Sonika; Kumar, Anant
ISBN: 9780443452543

portada Essential Kubeflow: Engineering ML Workflows on Kubernetes (en Inglés)

Essential Kubeflow: Engineering ML Workflows on Kubernetes (en Inglés)

Formato

Libro Físico

Editorial

Morgan Kaufmann Publishers

Autor

Josyula, Prashanth; Arora, Sonika; Kumar, Anant

Idioma

Inglés

N° páginas

250

Encuadernación

Tapa Blanda

ISBN13

9780443452543

Essential Kubeflow: Engineering ML Workflows on Kubernetes (en Inglés)

Josyula, Prashanth; Arora, Sonika; Kumar, Anant (Autor) · Morgan Kaufmann Publishers · Tapa Blanda

Libro Nuevo Importado

Envío: 23 a 31 días háb.

$ 343.42$ 206.05

-40%

Costos de importación incluídos en el precio ✅

Libro Nuevo

Quedan 100 unidades

$ 206.05

Llega entre el 01 Oct y el 16 Oct a Quito, Pichincha. Seleccionar ubicación

Agregar a lista de deseos

Reseña del libro "Essential Kubeflow: Engineering ML Workflows on Kubernetes (en Inglés)"

Essential Kubeflow: Engineering ML Workflows on Kubernetes provides the tools needed to transform ML workflows from experimental notebooks to production-ready platforms. Through hands-on examples and production-tested patterns, readers will master essential skills for building enterprise-grade Machine Learning platforms, including architecting production systems on Kubernetes, designing end-to-end ML pipelines, implementing robust model serving, efficiently scaling workloads, managing multi-user environments, deploying automated MLOps workflows, and integrating with existing ML tools. Whether you're a Machine Learning engineer looking to operationalize models, a platform engineer diving into ML infrastructure, or a technical leader architecting ML systems, this book provides solutions for real-world challenges. With this comprehensive guide to Kubeflow, a widely adopted open source MLOps platforms for automating ML workloads, readers will have the expertise to build and maintain scalable ML platforms that can handle the demands of modern enterprise AI initiatives.