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Building Machine Learning Pipelines : Automating Model Life Cycles with TensorFlow by Catherine Nelson and Hannes Hapke (2020, Trade Paperback)

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Building Machine Learning Pipelines : Automating Model Life Cycles with....

About this product

Product Identifiers

PublisherO'reilly Media, Incorporated
ISBN-101492053198
ISBN-139781492053194
eBay Product ID (ePID)22038384734

Product Key Features

Number of Pages275 Pages
LanguageEnglish
Publication NameBuilding Machine Learning Pipelines : Automating Model Life Cycles with Tensorflow
Publication Year2020
SubjectImage Processing, General, Data Processing
TypeTextbook
Subject AreaComputers, Science
AuthorCatherine Nelson, Hannes Hapke
FormatTrade Paperback

Dimensions

Item Height0.8 in
Item Weight22.5 Oz
Item Length9.2 in
Item Width7.2 in

Additional Product Features

Intended AudienceScholarly & Professional
LCCN2022-276253
Dewey Edition23
IllustratedYes
Dewey Decimal006.31
SynopsisCompanies are spending billions on machine learning projects, but it's money wasted if the models can't be deployed effectively. In this practical guide, Hannes Hapke and Catherine Nelson walk you through the steps of automating a machine learning pipeline using the TensorFlow ecosystem. You'll learn the techniques and tools that will cut deployment time from days to minutes, so that you can focus on developing new models rather than maintaining legacy systems. Data scientists, machine learning engineers, and DevOps engineers will discover how to go beyond model development to successfully productize their data science projects, while managers will better understand the role they play in helping to accelerate these projects. Understand the steps to build a machine learning pipeline Build your pipeline using components from TensorFlow Extended Orchestrate your machine learning pipeline with Apache Beam, Apache Airflow, and Kubeflow Pipelines Work with data using TensorFlow Data Validation and TensorFlow Transform Analyze a model in detail using TensorFlow Model Analysis Examine fairness and bias in your model performance Deploy models with TensorFlow Serving or TensorFlow Lite for mobile devices Learn privacy-preserving machine learning techniques
LC Classification NumberQ325.5

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