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

Показать описание

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

Jovian

Рекомендации по теме

Комментарии

You were very patient with the errors and delivery was perfect, hope to see more o these tutorials from you in the future, i learned a lot, thanks.

GeorgeHanta

i really thank you very much i had a presentation today and was not able to find a proper platform for deploying my model. thank u very much for this video

mvbxsmu

thank u for this video but, i stell have a problem,
i should integrate model automatique translation with flask in web app with pickle .
and he stell give to me error .
what is the solution
the probleme i think is with predict function

vbndtxu

Please answer, Can we give custom domain name in free version of render ?

AbhilashMSMPH

I am getting this error
No open ports detected, continuing to scan...

How to resolve this?

lokeshramdondapati

IN 41:00 mins you have changed some code that time i got confuse. Afterall, tutorial is awesome....✌😊

wmgvngi

How host it on server and run it from server only

Heroku is not free now😢😢
Please do it in different free served

stbs

you have written actions instead of action.

anishpandey

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

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

How to Deploy Machine Learning Models (ft. Runway)

Deploy ML model in 10 minutes. Explained

Deploy Machine Learning Models using Flask

Deploy ML model quickly and easily | Deploying machine learning models quickly and easily

Model Recommender - Design, Build & Deploy your ML Models 60% faster

Deploy Machine Learning Model Flask

268 - How to deploy your trained machine learning model into a local web application?

End to End Deploy Machine learning model Time Series usando Flask

Deploying Your ML Model

deploy machine learning model flask | on web page | full tutorial | step by step

Deploying a Machine Learning model as Dockerized API | ML model Deployment | MLOPS

How To Deploy Machine Learning Models Using FastAPI-Deployment Of ML Models As API’s

AWS re:Invent 2022 - [NEW] Easily build, train, and deploy ML models using geospatial data (AIM218)

Deploying Machine Learning Models at Scale in Cloud // Vishnu Prathish // MLOps Meetup #60

Deploy Machine Learning Model using Streamlit in Python | ML model Deployment

Deploying machine learning models on Kubernetes

THIS is HARDEST MACHINE LEARNING model I've EVER coded

ML Model Deployment With Flask On Heroku | How To Deploy Machine Learning Model With Flask | Edureka

AWS AMER Summit 2020 | Build, train, and deploy ML models with Amazon SageMaker

6 Easy steps to deploy Machine Learning (ML) models in AWS EC2 Instance

PyTorch in 100 Seconds

Deploy Machine Learning Model on Cloud - Udemy course

Deploy Machine Learning Model on Azure: A Step-by-Step Guide to Dockerized API Integration