DataHour: Deploying Models for Sentiment Analysis on Cloud

In this 4th part of the series on building & deploying sentiment analysis projects from scratch. We'll continue with the same Sentiment Analysis project and deploy the machine learning and deep learning models we built in the previous 3 sessions on cloud (AWS). 

Since we'll be using AWS as the cloud platform for deploying our Deep Learning Models,  we suggest you create an account on AWS and keep it ready before the session so that you can do hands-on work along with me:

• Create and activating a new AWS account: 
  https://aws.amazon.com/premiumsupport/knowledge-center/create-and-activate-aws-account/
• Get started with Amazon EC2 Linux instances: 
  https://docs.aws.amazon.com/AWSEC2/latest/UserGuide/EC2_GetStarted.html
• Connecting to your Linux instance from Windows using PuTTY: 
  https://docs.aws.amazon.com/AWSEC2/latest/UserGuide/EC2_GetStarted.html

If you have missed the previous session, you can catch up from the following recording links, and also download the code using the link below:

• Youtube recording link for the 1st part:  https://www.youtube.com/watch?v=4XqAK5HEobE
• Youtube recording link for the 2nd part: https://www.youtube.com/watch?v=FIkmqzHLWNk
• Youtube recording link for the 3rd part:  https://www.youtube.com/watch?v=2LiuhpKHp-k

Download the codes from: https://github.com/prashant9501/DataHour/tree/main/Sentiment%20Analysis%20Project

Prerequisites: Basic knowledge of Deep Learning will be helpful.

Prashant Sahu is a passionate Corporate Trainer & Consultant with more than 10 years of experience in Data Analytics, Machine Learning & Deep Learning applications. Currently working with Analytics Vidhya as Manager for Data Science Trainings, and is finishing his PhD from IIT Bombay.