Deploying ML Models in 60 Minutes using Python, Flask & Render | Step-by-Step Tutorial

Deployment Notebook: https://jovian.com/biraj/deploying-a-machine-learning-model Source Code: https://github.com/BirajCoder/practice-deployment/tree/main Model Training Notebook: https://jovian.com/birajde9/email-spam-classifier-naive-bayes Model Deployment is a critical phase in the machine learning pipeline where a developed model is made available in a production environment, enabling it to generate real-world predictions. The value of machine learning can only be actualized when a model is successfully deployed and integrated into a product or service. ​In this workshop, you'll delve into the process of deploying a machine learning model onto a web application using Flask, a leading Python web framework. By the end of the session, you'll have a firm grasp of the deployment process and be well-prepared to deploy your own models. Timestamps: 00:00 - Introduction 01:57 - Prerequisites and Problem Statement 3:39 - Project Setup on GitHub and Conda 12:02 - Create a Simple Flask Application 18:54 - Creating a Simple Form 23:25 - Sending a POST request 29:50 - Machine Learning Model 31:03 - Running the Model Locally 48:33 - Deploying the Flask Application on Render 56:52 - Creating an API route 1:05:15 - Code Refactoring 1:09:58 - Exercise 1:10:01 - Summary 1:12:20 - Questions ​Agenda: ​The workshop is organized into distinct segments as follows: ​1. Creating the First Web App Using Flask: Kick-start your Flask journey by creating your first web app. ​2. Adding Forms and Jinja Template: Learn to add forms to your web app and understand how to use Jinja for efficient template management. ​3. Deploying the ML Model Locally: Step-by-step guidance on deploying your pre-trained machine learning model on a local Flask server. ​4. Publishing the Web App Online: Once your model is deployed locally, learn the ins and outs of making it accessible online. ​5. Improving the Page Layout Using CSS: Lastly, discover how to use CSS to enhance the look and feel of your webpage. ​Speaker: Biraj De ​The workshop's speaker is a B.Tech grad from Kolkata, skilled in programming and data science. He started coding 7 years ago in languages like C, Java, Python, and JavaScript. Three years ago, he shifted to Data Science, after improving his problem-solving skills through competitions on platforms like Codechef, Hackerrank, and Leetcode. He attended multiple ML and Coding workshops/hackathons Now, for two years, he's been a dedicated data science teacher, guiding others in the exciting fields of Machine Learning and Data Science #ml #machinelearning #modeldeployment #deployment #python #flask #python3 #render #production #email #spam #classification

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