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Home Neural Networks

Deploying the machine learning model in Heroku using Flask

April 16, 2020
in Neural Networks
Deploying the machine learning model in Heroku using Flask
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Creating an API with Heroku is Simple one , you can do it very quickly.

Now we are going to create an API for sentiment analysis , you can also alternate the code any machine learning model

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I created a folder name as sentiment_analysis

At minimum level your file should contain these .

we will get those one by one

Sentiment Analysis

this is an simple flask app for giving the result the text is positive or negative or neutral , just save this and run the app.py

server

then open the jupyter or python editor and another side this server to be running parallel .

just ignore it

The main thing you have to keep in mind that we have to send the data in json format .

In this we just converted the data into json format

After that i just requested the running server with its address and passing the data with it.

We got answer as positive . It is working , Now we have to deploy this to Heroku.

Create a new account in Heroku if you did not have it

https://dashboard.heroku.com/apps

After Creating the account Click on new.

Click the Create new app

Select the name which is available and Create the new app

Then install the Heroku-CLI in your system

For windows 32bit https://cli-assets.heroku.com/heroku-x86.exe

For windows 64bit https://cli-assets.heroku.com/heroku-x64.exe

For Ubuntu 16+ sudo snap install --classic heroku

For Mac brew tap heroku/brew && brew install heroku

For more info https://devcenter.heroku.com/articles/heroku-cli

Ok now we are ready to deploy but we need create two more files in it

web: gunicorn app:app

Procfile [P has to be in caps]

you can create the requirements.txt by this command

pip freeze > requirements.txt
At least you should have these modules for this API

We are ready to deploy it ,This is how our folder finally looks like

Then do the below steps in your cmd

$ heroku login

the it will popup the login in access in browser click login to it

$ cd sentiment_analysis/
$ git init
$ heroku git:remote -a sentimentsts

Deploy your application

Commit your code to the repository and deploy it to Heroku using Git.

$ git add .
$ git commit -am "make it better"
$ git push heroku master

Everything is done, Click the open app in your app page , you will get the link of the API

Finallyyyyy..

Credit: BecomingHuman By: Salman Faroz

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