NLP Challenge - IMDB Dataset of 50K Movie Reviews to perform Sentiment analysis

This solution is based on the IMDB Dataset of 50K Movie Reviews. The dataset is used to perform sentiment analysis on the movie reviews. The trained model is served as a REST API using FastAPI and dockerized using Docker.

You can find the API hosted at https://sentiment-analysis.astro-dev.tech

Tech Stack

• Python 3.12
• Scikit-learn
• Pandas
• FastAPI
• Docker

Training the Model

The model is trained using a dataset of 50K IMDB reviews:

• Open the app/sentiment_analysis.ipynb notebook.
• Follow the steps for Exploratory Data Analysis (EDA) and model training.
• Save the trained model and vectorizer as .pkl files in the models directory.

API endpoints

• GET /: Returns a welcome message
• POST /analyze/: Perform sentiment analysis on the input text

Installation

Make sure to execute all the cells in the notebook (app/sentiment_analysis.ipynb) sequentially to train and save the model before running the API.

Using docker

1. Build the docker image

docker build -t imdb-sentiment-analysis .

2. Run the docker image

docker run -p 8000:8000 imdb-sentiment-analysis

3. Access the API

http POST localhost:8000/analyze input_text="i really like react hooks" --follow

Using pip

1. Install the requirements

pip install -r requirements.txt

2. Run the app

python app/main.py

3. Access the API

http POST localhost:8000/analyze input_text="i really like react hooks" --follow