Build Short Video Recommendation System For Flutter App

# Project Summary: Short Video Recommendation TensorFlow Lite Model

# Objective:
Create a TensorFlow Lite model for short video recommendations in a Flutter app, using Firebase Firestore as the database and Firebase ML for deployment.

# Requirements:*
1. Recommend videos based on user's liked videos, excluding watched videos.
2. Include popular content to prevent user from getting stuck on the same topic.
3. Use Firebase Firestore to store video data and user interactions.

# Workflow:
1. Fetch video data and user interactions from Firestore.
2. Calculate similarity scores between liked videos and remaining videos.
3. Include popular content in recommendations.
4. Train and deploy the model using Firebase ML.

# Deliverables:
1. TensorFlow Lite model for video recommendations.
2. Integration with Firebase Firestore and Firebase ML.
3. Documentation on model deployment and usage in the app.

# Additional Notes:
- Ensure compatibility with Flutter for app integration.
- Optimize model for performance on mobile devices.
- Consider user privacy and data security in model implementation.