How to deploy Machine Learning model as a Rest API? | Flask Rest API | Integrate in existing web app
In this video you will learn how to deploy your Machine Learning models as a REST API. The deployment of your models is a crucial step in the ML workflow and it is the point when your models actually become useful to your company.
I will cover how to convert your Model to a REST API so the users can consume them in a production environment. We will focus on solutions converting the model to a FLASK REST API. I will cover the Simple Linear Regression model but the concepts can be easily transferred to other Models and frameworks.
Link to medium article on this topic: / deploy-machine-learning-model-as-a-rest-ap...
Link to code GitHub: https://github.com/hnawaz007/pythonda...
Link to Simple Linear Regression video: • Machine Learning: Python Simple Linea...
Link to previous video with model conversion to pickle file: • Flask build data science app | deploy...
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#MachineLearning #RESTAPI #SimpleLinearRegression
Topics covered in this video:
0:00 - Agenda : Introduction
1:05 - Preview of complete app
1:37 - Get Model file
1:54 - Create new project + setup
3:41 - Model prediction class
5:42 - Get Model data class
6:22 - Run & Test API
6:55 Rest API Web integration