Open Daily: 10am - 10pm | Alley door pickup 10am - 7pm 3038 Hennepin Ave Minneapolis, MN
612-822-4611

  • Open Daily: 10am - 10pm
    Alley-side Pickup: 10am - 7pm

    3038 Hennepin Ave Minneapolis, MN
    612-822-4611

Open Daily: 10am - 10pm | Alley-side Pickup: 10am - 7pm
3038 Hennepin Ave Minneapolis, MN
612-822-4611
Beginning MLOps with Mlflow: Deploy Models in AWS Sagemaker, Google Cloud, and Microsoft Azure

Beginning MLOps with Mlflow: Deploy Models in AWS Sagemaker, Google Cloud, and Microsoft Azure

Alla, Sridhar
Adari, Suman Kalyan

Paperback

General ComputersProbability & StatisticsProgramming

Publisher Price: $64.99

ISBN10: 1484265483
ISBN13: 9781484265482
Publisher: Apress
Published: Dec 8 2020
Pages: 330
Weight: 1.07
Height: 0.72 Width: 6.14 Depth: 9.21
Language: English
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.

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