Isbn: 9781492050124 - kubeflow for machine learning: from lab to production (23 Ergebnisse)

paperback. Zustand: Good. Light wear to edges. Overall good condition. Ships next business day from NC.

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. New Copy. Customer Service Guaranteed.

Zustand: New. Brand New! Not Overstocks or Low Quality Book Club Editions! Direct From the Publisher! We're not a giant, faceless warehouse organization! We're a small town bookstore that loves books and loves it's customers! Buy from Lakeside Books.

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.…

Paperback or Softback. Zustand: New. Kubeflow for Machine Learning: From Lab to Production. Book.

PAP. Zustand: New. New Book. Shipped from UK. Established seller since 2000.

Zustand: New.

Zustand: As New. Unread book in perfect condition.

PAP. Zustand: New. New Book. Shipped from UK. Established seller since 2000.

Paperback. Zustand: Used; Good. ***Simply Brit*** Welcome to our online used book store, where affordability meets great quality. Dive into a world of captivating reads without breaking the bank. We take pride in offering a wide selection of used books, from classics to hidden gems, ensuring there is something for every literary palate. All orders are shipped within 24 hours and our lightning fast-delivery within 48 hours coupled with our prompt customer service ensures a smooth journey from ordering to delivery. Discover the joy of reading with us, your trusted source for affordable books that do not compromise on quality.…

Zustand: New.

Zustand: As New. Unread book in perfect condition.

Paperback / softback. Zustand: New. New copy - Usually dispatched within 4 working days.

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

Zustand: New. 2020. Paperback. . . . . .

Zustand: New. In English.

Zustand: New. 2020. Paperback. . . . . . Books ship from the US and Ireland.

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.…

Taschenbuch. Zustand: Neu. Neuware - 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 solves- Understand the differences between Kubeflow on different cluster types- Train models using Kubeflow with popular tools including Scikit-learn, TensorFlow, and Apache Spark- Keep your model up to date with Kubeflow Pipelines- Understand how to capture model training metadata- Explore how to extend Kubeflow with additional open source tools- Use hyperparameter tuning for training- Learn how to serve your model in production. …

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.