This project explores machine learning and automation using YouTube data.
It uses the YouTube-DL library and Python data tools to extract video information and perform style-based analysis or transformation.
The goal is to experiment with AI-driven insights or styling tasks on YouTube videos — such as analyzing metadata, visual trends, or integrating ML models for pattern recognition.
- Python
- YouTube-DL for data extraction
- Pandas for data handling
- Matplotlib / Seaborn for visualization
- Jupyter Notebook for experimentation
- Fetch YouTube video metadata (title, views, likes, duration, etc.)
- Analyze video statistics and trends
- Apply ML or data preprocessing techniques for insights
- Visualize patterns in user engagement or video content
- Clone the repository
git clone https://github.com/Akashyadav-aiml/YouTube-ML-Lab.git cd YouTube-ML-Lab