Overview
- Guides you in transitioning from traditional machine learning to machine learning productionization
- Covers the entire range of deployment options, including Flask, Streamlit, Docker, and Kubernetes
- Presents the process to wrap and containerize any machine learning model
Access this book
Tax calculation will be finalised at checkout
Other ways to access
Table of contents (5 chapters)
Keywords
About this book
This book begins with a focus on the machine learning model deployment process and its related challenges. Next, it covers the process of building and deploying machine learning models using different web frameworks such as Flask and Streamlit. A chapter on Docker follows and covers how to package and containerize machine learning models. The book also illustrates how to build and train machine learning and deep learning models at scale using Kubernetes.
The book is a good starting point for people who want to move to the next level of machine learning by taking pre-built models and deploying them into production. It also offers guidance to those who want to move beyond Jupyter notebooks to training models at scale on cloud environments. All the code presented in the book is available in the form of Python scripts for you to try the examples and extend them in interesting ways.
What You Will Learn
- Build, train, and deploy machine learning models at scale using Kubernetes
- Containerize any kind of machine learning model and run it on any platform using Docker
- Deploy machine learning and deep learning models using Flask and Streamlit frameworks
Who This Book Is For
Data engineers, data scientists, analysts, and machine learning and deep learning engineers
Authors and Affiliations
About the author
Manager of Data Science at Bain & Company. He has over 11 years of experience in the data science field working with multiple product- and service-based organizations. He has been part of numerous ML and AI large-scale projects. He has published three books on large scale data processing and machine learning. He is a regular speaker at major AI conferences.
Bibliographic Information
Book Title: Deploy Machine Learning Models to Production
Book Subtitle: With Flask, Streamlit, Docker, and Kubernetes on Google Cloud Platform
Authors: Pramod Singh
DOI: https://doi.org/10.1007/978-1-4842-6546-8
Publisher: Apress Berkeley, CA
eBook Packages: Professional and Applied Computing, Apress Access Books, Professional and Applied Computing (R0)
Copyright Information: Pramod Singh 2021
Softcover ISBN: 978-1-4842-6545-1Published: 15 December 2020
eBook ISBN: 978-1-4842-6546-8Published: 14 December 2020
Edition Number: 1
Number of Pages: XIII, 150
Number of Illustrations: 115 b/w illustrations
Topics: Machine Learning, Python, Open Source