Sentiment Analysis

Sentiment Analysis for tweets

Steps to run the pipeline

Create virtual conda environment

After creating virtual environment, install python version>=3.8

conda create -n sentiment

Install requirements

Install all the required dependencies from requirements.txt file

pip install -r requirements.txt

Train model

• Create folder named data
• Add training data in csv format to the folder
• run training.py script

python training.py

Start FastAPI server

uvicorn app:app --reload

Hit the url with the text whose sentiment needs to be identified, the api returns a dictonary with the text and its predicted sentiment

Future Work

• Create support for CLI
• Make the pipeline adaptive to dynamic data inputs