Filonenko ilan (12 Ergebnisse)

Paperback. Zustand: Very Good. 1. It's a well-cared-for item that has seen limited use. The item may show minor signs of wear. All the text is legible, with all pages included. It may have slight markings and/or highlighting.

Soft cover. Zustand: Very Good. 1st Edition. Putting machine models of learning into action.

Zustand: New.

Paperback. Zustand: New. If you're training a machine learning model but aren't sure how to put it into production, this book will get you there. Kubeflow provides a collection of cloud native tools for different stages of a model's lifecycle, from data exploration, feature preparation, and model training to model serving. This guide helps data scientists build production-grade machine learning implementations with Kubeflow and shows data engineers how to make models scalable and reliable.Using examples throughout the book, authors Holden Karau, Trevor Grant, Ilan Filonenko, Richard Liu, and Boris Lublinsky explain how to use Kubeflow to train and serve your machine learning models on top of Kubernetes in the cloud or in a development environment on-premises. Understand Kubeflow's design, core components, and the problems it solvesLearn how to set up Kubeflow on a cloud provider or on an in-house clusterTrain models using Kubeflow with popular tools including scikit-learn, TensorFlow, and Apache SparkLearn how to add custom stages such as serving and predictionKeep your model up-to-date with Kubeflow PipelinesUnderstand how to validate machine learning pipelines.…

Zustand: New.

Zustand: As New. Unread book in perfect condition.

Zustand: New.

Zustand: As New. Unread book in perfect condition.

Paperback. Zustand: Brand New. 239 pages. 9.00x7.00x0.75 inches. In Stock.

Zustand: New. In English.

Paperback. Zustand: New. If you're training a machine learning model but aren't sure how to put it into production, this book will get you there. Kubeflow provides a collection of cloud native tools for different stages of a model's lifecycle, from data exploration, feature preparation, and model training to model serving. This guide helps data scientists build production-grade machine learning implementations with Kubeflow and shows data engineers how to make models scalable and reliable.Using examples throughout the book, authors Holden Karau, Trevor Grant, Ilan Filonenko, Richard Liu, and Boris Lublinsky explain how to use Kubeflow to train and serve your machine learning models on top of Kubernetes in the cloud or in a development environment on-premises. Understand Kubeflow's design, core components, and the problems it solvesLearn how to set up Kubeflow on a cloud provider or on an in-house clusterTrain models using Kubeflow with popular tools including scikit-learn, TensorFlow, and Apache SparkLearn how to add custom stages such as serving and predictionKeep your model up-to-date with Kubeflow PipelinesUnderstand how to validate machine learning pipelines.…

Zustand: New. This guide helps data scientists build production-grade machine learning implementations with Kubeflow and shows data engineers how to make models scalable and reliable&Uumlber den AutorrnrnTrevor Grant is a member of the Apache Sof.