Beginning MLOps with MLFlow

Deploy Models in AWS SageMaker, Google Cloud, and Microsoft Azure

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,

Éditeur :

Apress


Paru le : 2020-12-07



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Description

Integrate MLOps principles into existing or future projects using MLFlow, operationalize your models, and deploy them in AWS SageMaker, Google Cloud, and Microsoft Azure. ?This book guides you through the process of data analysis, model construction, and training.


The authors begin by introducing you to basic data analysis on a credit card data set and teach you how to analyze the features and their relationships to the target variable. You will learn how to build logistic regression models in scikit-learn and PySpark, and you will go through the process of hyperparameter tuning with a validation data set. You will explore three different deployment setups of machine learning models with varying levels of automation to help you better understand MLOps. MLFlow is covered and you will explore how to integrate MLOps into your existing code, allowing you to easily track metrics, parameters, graphs, and models. You will be guided through the process of deploying and querying your models with AWS SageMaker, Google Cloud, and Microsoft Azure. And you will learn how to integrate your MLOps setups using Databricks.







What You Will Learn
Perform basic data analysis and construct models in scikit-learn and PySparkTrain, test, and validate your models (hyperparameter tuning)Know what MLOps is and what an ideal MLOps setup looks likeEasily integrate MLFlow into your existing or future projectsDeploy your models and perform predictions with them on the cloud



Who This Book Is For


Data scientists and machine learning engineers who want to learn MLOps and know how to operationalize their models

Pages
330 pages
Collection
n.c
Parution
2020-12-07
Marque
Apress
EAN papier
9781484265482
EAN PDF
9781484265499

Informations sur l'ebook
Nombre pages copiables
3
Nombre pages imprimables
33
Taille du fichier
10701 Ko
Prix
62,11 €
EAN EPUB
9781484265499

Informations sur l'ebook
Nombre pages copiables
3
Nombre pages imprimables
33
Taille du fichier
14438 Ko
Prix
62,11 €

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