Overview
- Covers the concepts behind MLOps that you need to know to operationalize your machine learning solutions for practical use
- Shows you how to deploy models with AWS SageMaker, Google Cloud, and Microsoft Azure
- Explains MLFlow with PyTorch, Keras, and TensorFlow
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Table of contents (7 chapters)
Keywords
About this book
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 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
Who This Book Is For
Data scientists and machine learning engineers who want to learn MLOps and know how to operationalize their models
Authors and Affiliations
About the authors
Suman Kalyan Adari is an undergraduate student pursuing a BS degree in computer science atthe University of Florida. He has been conducting deep learning research in the field of cybersecurity since his freshman year, and has presented at the IEEE Dependable Systems and Networks workshop on Dependable and Secure Machine Learning held in Portland, Oregon, USA in June of 2019. He is passionate about deep learning, and specializes in its practical uses in various fields such as image recognition, anomaly detection, natural language processing, targeted adversarial attacks, and more.
Bibliographic Information
Book Title: Beginning MLOps with MLFlow
Book Subtitle: Deploy Models in AWS SageMaker, Google Cloud, and Microsoft Azure
Authors: Sridhar Alla, Suman Kalyan Adari
DOI: https://doi.org/10.1007/978-1-4842-6549-9
Publisher: Apress Berkeley, CA
eBook Packages: Professional and Applied Computing, Apress Access Books, Professional and Applied Computing (R0)
Copyright Information: Sridhar Alla, Suman Kalyan Adari 2021
Softcover ISBN: 978-1-4842-6548-2Published: 08 December 2020
eBook ISBN: 978-1-4842-6549-9Published: 07 December 2020
Edition Number: 1
Number of Pages: XIV, 330
Number of Illustrations: 267 b/w illustrations
Topics: Machine Learning, Professional Computing