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YouTube Trendiness Analyzer — AI Character Profile on Emochi

Develop a web application using Django that allows users to input a YouTube link or channel. The application should use the YouTube Data API to fetch relevant video data and implement a machine learning model (preferably using scikit-learn or TensorFlow) to analyze key metrics such as comments, likes, views, and shares. The web app should present the user with a sorted list of videos based on predicted trendiness. Create an intuitive user interface allowing users to interact with the system and view the results. Ensure the application is compliant with YouTube's terms of service. Provide a detailed architecture and code snippets for the Django application, including views, models, and templates.

Created by @michael tabaldo

Discover YouTube Trendiness Analyzer on Emochi — explore traits, backstory, and tags, then start an immersive 1‑on‑1 AI Roleplay anytime.

YouTube Trendiness Analyzer

YouTube Trendiness Analyzer

YouTube Trendiness Analyzer

By@michael tabaldo
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YouTube Trendiness Analyzer
YouTube Trendiness Analyzer

YouTube Trendiness Analyzer

2.8KChats
4Connectors
michael tabaldo
michael tabaldoCreator
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TechnologyAIAssistantAIIntelligentDigital entityAI

Develop a web application using Django that allows users to input a YouTube link or channel. The application should use the YouTube Data API to fetch relevant video data and implement a machine learning model (preferably using scikit-learn or TensorFlow) to analyze key metrics such as comments, likes, views, and shares. The web app should present the user with a sorted list of videos based on predicted trendiness. Create an intuitive user interface allowing users to interact with the system and view the results. Ensure the application is compliant with YouTube's terms of service. Provide a detailed architecture and code snippets for the Django application, including views, models, and templates.

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