I Coded a YouTube AI Assistant That Boosted My Productivity

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A step-by-step tutorial in Python

Have you ever ever found yourself able where you needed to sift through a whole lot of YouTube videos to learn or research about a specific topic? Watching hours and hours of videos, taking notes, and still overlooking essential details is a real struggle.

In this text, I’ll go over the strategy of how I saved countless hours extracting key information from YouTube videos. I did this by constructing a Python workflow that makes use of enormous language models (LLMs) to reply any questions on the video content. This not only saved me hours, however it also boosted my productivity and enhanced my learning. Because of this, I can use the time beyond regulation to create more content or take a well-deserved break.

Let me walk you thru the strategy of how I created this YouTube AI assistant. Let’s dive in!

Before proceeding to the technicalities, let’s explore why this project has been a game-changer for me.

On the core of what I’m doing each day in my full-time role as a developer advocate and in my part-time endeavor as a YouTuber (I run the Data Professor YouTube channel) is content research.

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