Deploy Machine Learning Models to Production

With Flask, Streamlit, Docker, and Kubernetes on Google Cloud Platform

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Éditeur :

Apress


Paru le : 2020-12-14



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Description
Build and deploy machine learning and deep learning models in production with end-to-end examples.


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 KubernetesContainerize any kind of machine learning model and run it on any platform using DockerDeploy 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


Pages
150 pages
Collection
n.c
Parution
2020-12-14
Marque
Apress
EAN papier
9781484265451
EAN PDF
9781484265468

Informations sur l'ebook
Nombre pages copiables
1
Nombre pages imprimables
15
Taille du fichier
5427 Ko
Prix
46,34 €
EAN EPUB
9781484265468

Informations sur l'ebook
Nombre pages copiables
1
Nombre pages imprimables
15
Taille du fichier
6021 Ko
Prix
46,34 €

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