03142nam 2200493 450 991048356850332120210320133409.01-4842-6549-110.1007/978-1-4842-6549-9(CKB)4100000011645142(DE-He213)978-1-4842-6549-9(MiAaPQ)EBC6421904(CaSebORM)9781484265499(PPN)252518586(EXLCZ)99410000001164514220210320d2021 uy 0engurnn|008mamaatxtrdacontentcrdamediacrrdacarrierBeginning MLOps with MLFlow deploy models in aws sagemaker, google cloud, and microsoft azure /Sridhar Alla, Suman Kalyan Adari1st ed. 2021.Berkeley, California :APress,[2021]©20211 online resource (XIV, 330 p. 267 illus.) Includes index.1-4842-6548-3 Chapter 1: Getting Started: Data Analysis -- Chapter 2: Building Models -- Chapter 3: What Is MLOps? -- Chapter 4: Introduction to MLFlow -- Chapter 5: Deploying in AWS -- Chapter 6: Deploying in Azure -- Chapter 7: Deploying in Google -- Appendix A: a2ml.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. You will: Perform basic data analysis and construct models in scikit-learn and PySpark Train, test, and validate your models (hyperparameter tuning) Know what MLOps is and what an ideal MLOps setup looks like Easily integrate MLFlow into your existing or future projects Deploy your models and perform predictions with them on the cloud.Computer softwareMachine learningComputer software.Machine learning.006.31Alla Sridhar886225Adari Suman KalyanMiAaPQMiAaPQMiAaPQBOOK9910483568503321Beginning MLOps with MLFlow2854325UNINA