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Can I read Deploy Machine Learning Models to Production : With Flask, Streamlit, Docker, and Kubernetes on Google Cloud Platform on EtoBox?

Deploy Machine Learning Models to Production : With Flask, Streamlit, Docker, and Kubernetes on Google Cloud Platform by Pramod Singh is a nonfiction available to read on EtoBox.

What is Deploy Machine Learning Models to Production : With Flask, Streamlit, Docker, and Kubernetes on Google Cloud Platform about?

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 Kubernetes Containerize any kind of machine learning model and run it on any platform using Docker Deploy machine learning

Who reads Deploy Machine Learning Models to Production : With Flask, Streamlit, Docker, and Kubernetes on Google Cloud Platform?

It is typically read by self-directed learners exploring a subject in depth.

Common subject areas: history, science, philosophy, social sciences.

Author
Pramod Singh
Publisher
Apress : Imprint: Apress
Published
2020
Language
EN
ISBN
9781484265475
Category
nonfiction
Subjects
Computer Science, Mathematics, Language Learning

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