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Lingua: Inglese
Editore: Packt Publishing 3/18/2022, 2022
ISBN 10: 1801074488 ISBN 13: 9781801074483
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Paperback or Softback. Condizione: New. Reproducible Data Science with Pachyderm: Learn how to build version-controlled, end-to-end data pipelines using Pachyderm 2.0. Book.
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Aggiungi al carrelloCondizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Pachyderm enables you to create collaborative data science workflows and reproduce your experiments at scale. This book will help you leverage Pachyderm s data versioning and lineage features to build scalable end-to-end AI/ML pipelines and show you how to .
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Aggiungi al carrelloTaschenbuch. Condizione: Neu. Reproducible Data Science with Pachyderm | Learn how to build version-controlled, end-to-end data pipelines using Pachyderm 2.0 | Svetlana Karslioglu | Taschenbuch | Kartoniert / Broschiert | Englisch | 2022 | Packt Publishing | EAN 9781801074483 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu Print on Demand.
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Aggiungi al carrelloTaschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Create scalable and reliable data pipelines easily with Pachyderm Key Features:Learn how to build an enterprise-level reproducible data science platform with Pachyderm Deploy Pachyderm on cloud platforms such as AWS EKS, Google Kubernetes Engine, and Microsoft Azure Kubernetes Service Integrate Pachyderm with other data science tools, such as Pachyderm Not Elektronisches Buch Book Description: Pachyderm is an open source project that enables data scientists to run reproducible data pipelines and scale them to an enterprise level. This book will teach you how to implement Pachyderm to create collaborative data science workflows and reproduce your ML experiments at scale. You'll begin your journey by exploring the importance of data reproducibility and comparing different data science platforms. Next, you'll explore how Pachyderm fits into the picture and its significance, followed by learning how to install Pachyderm locally on your computer or a cloud platform of your choice. You'll then discover the architectural components and Pachyderm's main pipeline principles and concepts. The book demonstrates how to use Pachyderm components to create your first data pipeline and advances to cover common operations involving data, such as uploading data to and from Pachyderm to create more complex pipelines. Based on what you've learned, you'll develop an end-to-end ML workflow, before trying out the hyperparameter tuning technique and the different supported Pachyderm language clients. Finally, you'll learn how to use a SaaS version of Pachyderm with Pachyderm Not Elektronisches Buch. By the end of this book, you will learn all aspects of running your data pipelines in Pachyderm and manage them on a day-to-day basis. What You Will Learn:Understand the importance of reproducible data science for enterprise Explore the basics of Pachyderm, such as commits and branches Upload data to and from Pachyderm Implement common pipeline operations in Pachyderm Create a real-life example of hyperparameter tuning in Pachyderm Combine Pachyderm with Pachyderm language clients in Python and Go Who this book is for: This book is for new as well as experienced data scientists and machine learning engineers who want to build scalable infrastructures for their data science projects. Basic knowledge of Python programming and Kubernetes will be beneficial. Familiarity with Golang will be helpful.