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YouTube Trend Analyzer

An AI-powered web application that helps content creators and casual viewers understand what’s trending on YouTube and predict how videos will perform — all in one place.

It combines machine learning predictions,real-time YouTube Data API analytics, and natural language summarization to save hours of manual research.

Features

  • 30-Day View Prediction – Predict future views of any YouTube video using a trained ML regression model.
  • AI Summaries – Instantly summarize trending videos so you can grasp the content without watching it.
  • Category & Filter Search – Browse trending videos by category, with an option to exclude Shorts.
  • Real-time Analytics – Fetch live statistics (views, likes, comments, etc.) directly from YouTube.
  • Content Creators's Help – Understand why videos trend and plan content strategically.

Tech Stack

  • Frontend: HTML5, CSS3, JavaScript
  • Backend: Flask (Python)
  • Machine Learning: Scikit-learn, Joblib, Pandas, NumPy
  • NLP: Hugging Face Transformers, NLTK
  • API: YouTube Data API v3 (Google API Python Client)
  • Models:
    • sshleifer/distilbart-cnn-12-6 (fine-tuned for summarization)
    • Gradient Boosting Regressor (view prediction)

Usage

  • To Analyze a Video: Paste the YouTube video URL → Fetch stats → Get AI summary + 30-day view prediction.

  • To Browse Trending Content: Select category → View summaries + performance estimates for top trending videos.

Model Performance

  • Summarization: Fine-tuned DistilBART model evaluated using ROUGE scores.
  • Prediction Model: Gradient Boosting Regressor with R² = 0.7984 (explains ~80% of variation).

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An attempt to Analyze Youtube Trends

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