{"product_id":"deploy-machine-learning-models-to-production-with-flask-streamlit-docker-and-kubernetes-on-google-cloud-platform-9781484265451","title":"Deploy Machine Learning Models to Production: With Flask, Streamlit, Docker, and Kubernetes on Google Cloud Platform","description":"Chapter 1: Configuring Your Deployment Environment\u003cbr\u003eChapter goal: This chapter covers the steps right from reading the data, pre-processing, feature engineering, model training and prediction on local as well as on the cloud. This chapter provides the audience with a set of required libraries and code\/data download information so that the user can set up their environment appropriately. \u003cp\u003e\u003c\/p\u003eSub -Topics\u003cbr\u003e- Configuring your development environment\u003cbr\u003e- Installing required libraries\u003cbr\u003e- Building Python and TensorFlow based models \u003cp\u003e\u003c\/p\u003eChapter 2: Introduction to Model Deployment and Challenges\u003cbr\u003eNo of pages: 20\u003cbr\u003eChapter goal: The chapter showcases what is meant by deployment and what are the challenges associated with it.\u003cbr\u003eSub - Topics\u003cbr\u003e- Understanding model deployment\u003cbr\u003e- Understanding challenges\u003cbr\u003e- Serverless architecture for deployment \u003cp\u003e\u003c\/p\u003e \u003cp\u003e\u003c\/p\u003eChapter 3: Model Deployment Using Flask\u003cbr\u003eNo of pages: 25\u003cbr\u003eChapter goal: This chapter covers the lightweight web framework - Flask for deploying the small and simple machine learning models. \u003cp\u003e\u003c\/p\u003eSub - Topics: \u003cbr\u003e- What is Flask\u003cbr\u003e- Build Python-based model\u003cbr\u003e- Deploy machine learning model using Flask \u003cp\u003e\u003c\/p\u003eChapter 4: Model Containerization Using Docker\u003cbr\u003eNo of pages:30\u003cbr\u003eChapter goal: This chapter is devoted to the understanding of docker platform. It covers all the steps to containerize any model, application using docker. \u003cp\u003e\u003c\/p\u003eSub - Topics: \u003cbr\u003e- Introduction to Docker\u003cbr\u003e- Build a custom Docker image\u003cbr\u003e- Run a machine Learning model using Docker \u003cp\u003e\u003c\/p\u003e \u003cp\u003e\u003c\/p\u003eChapter 5: Introduction to Kubeflow\u003cbr\u003eNo of pages:30 \u003cp\u003e\u003c\/p\u003eChapter goal: This chapter serves as an introduction to our core theme of the book: Build and deploy machine learning models using Kubeflow. The chapter begins with covering various components of Kubeflow and offers information on its advantages over other platforms\u003cbr\u003eSub - Topics: \u003cbr\u003e- Gentle Introduction to Kubernetes\u003cbr\u003e- Introduction to Kubeflow\u003cbr\u003e- Kubeflow components \u003cp\u003e\u003c\/p\u003e \u003cp\u003e\u003c\/p\u003eChapter 6: Model Deployment Using Kubeflow\u003cbr\u003eNo of pages: 35 \u003cp\u003e\u003c\/p\u003eChapter goal: This chapter focuses on the industrial implementation of deep learning model in the Google Cloud Platform using Kubeflow. This chapter also demonstrates various techniques like hyperparameter tuning and workflows for training and serving the models for predictions\u003cbr\u003eSub - Topics: \u003cp\u003e\u003c\/p\u003e- Google Cloud Platform configuration\u003cbr\u003e- Hyperparameter tuning of the model\u003cbr\u003e- Training and serving model at scale \u003cp\u003e\u003c\/p\u003eChapter 7: Model Deployment Using MLflow \u003cp\u003e\u003c\/p\u003eNo of pages:20\u003cbr\u003eChapter goal: This chapter covers the alternative to Google's Kube\u003cbr\u003e\u003cbr\u003e\u003cb\u003eAuthor:\u003c\/b\u003e \u003ca href=\"https:\/\/correctionsbookstore.com\/search?type=product%2Carticle%2Cpage\u0026amp;q=AUTH-12056438\"\u003ePramod Singh\u003c\/a\u003e\u003cbr\u003e\u003cb\u003ePublisher:\u003c\/b\u003e Apress\u003cbr\u003e\u003cb\u003ePublished:\u003c\/b\u003e 01\/01\/2021\u003cbr\u003e\u003cb\u003ePages:\u003c\/b\u003e 150\u003cbr\u003e\u003cb\u003eBinding Type:\u003c\/b\u003e Paperback\u003cbr\u003e\u003cb\u003eWeight:\u003c\/b\u003e 0.53lbs\u003cbr\u003e\u003cb\u003eSize:\u003c\/b\u003e 9.21h x 6.14w x 0.35d\u003cbr\u003e\u003cb\u003eISBN13:\u003c\/b\u003e 9781484265451\u003cbr\u003e\u003cb\u003eISBN10:\u003c\/b\u003e 1484265459\u003cbr\u003e\u003cb\u003eBISAC Categories:\u003c\/b\u003e\u003cbr\u003e- \u003ca href=\"https:\/\/correctionsbookstore.com\/search?type=product%2Carticle%2Cpage\u0026amp;q=CAT-COM\"\u003eComputers\u003c\/a\u003e | \u003ca href=\"https:\/\/correctionsbookstore.com\/search?type=product%2Carticle%2Cpage\u0026amp;q=BISAC-COM051360\"\u003eLanguages | Python\u003c\/a\u003e\u003cbr\u003e- \u003ca href=\"https:\/\/correctionsbookstore.com\/search?type=product%2Carticle%2Cpage\u0026amp;q=CAT-COM\"\u003eComputers\u003c\/a\u003e | \u003ca href=\"https:\/\/correctionsbookstore.com\/search?type=product%2Carticle%2Cpage\u0026amp;q=BISAC-COM004000\"\u003eArtificial Intelligence | General\u003c\/a\u003e\u003cbr\u003e- \u003ca href=\"https:\/\/correctionsbookstore.com\/search?type=product%2Carticle%2Cpage\u0026amp;q=CAT-COM\"\u003eComputers\u003c\/a\u003e | \u003ca href=\"https:\/\/correctionsbookstore.com\/search?type=product%2Carticle%2Cpage\u0026amp;q=BISAC-COM051390\"\u003eProgramming | Open Source\u003c\/a\u003e\u003cbr\u003e\u003cbr\u003e\u003cp\u003e\u003cb\u003eAbout the Author\u003c\/b\u003e\u003cbr\u003e\u003cb\u003ePramod Singh\u003c\/b\u003e is Manager of Data Science at Bain \u0026amp; Company. Previously, he worked as Sr. Machine Learning Engineer at Walmart Labs and Data Science Manager at Publicis Sapient in India. He has spent over 10 years working in machine learning, deep learning, data engineering, algorithm design, and application development. He has authored three Apress books: \u003ci\u003eMachine Learning with PySpark\u003c\/i\u003e, \u003ci\u003eLearn PySpark, \u003c\/i\u003eand \u003ci\u003eLearn TensorFlow 2.0\u003c\/i\u003e. He is a regular speaker at major conferences such as O'Reilly's Strata Data, GIDS, and other AI conferences. He is an active mentor and faculty in machine learning and AI at various educational institutes. He lives in Bangalore with his wife and four-year-old son. In his spare time, he enjoys playing guitar, coding, reading, and watching football. \u003c\/p\u003e\u003cp\u003e\u003c\/p\u003eManager of Data Science at Bain \u0026amp; 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.\u003cbr\u003e","brand":"Apress","offers":[{"title":"Default Title","offer_id":45876729544879,"sku":"9781484265451","price":44.99,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0651\/9255\/8767\/files\/img_f9264ce9-08f0-436d-848d-0e0524fe2b7b.jpg?v=1757694656","url":"https:\/\/www.correctionsbookstore.com\/es\/products\/deploy-machine-learning-models-to-production-with-flask-streamlit-docker-and-kubernetes-on-google-cloud-platform-9781484265451","provider":"Corrections Bookstore ","version":"1.0","type":"link"}