How to Build ML Solutions (w/ Python Code Walkthrough)
🤝 Your team not maximizing Claude? I run 1:1 and team AI workshops for companies doing $10M+ per year: https://aibuilder.academy/yt/6qCrvlHRhcM
This is the 4th video in a series on Full Stack Data Science. Here, I explain why experimentation is critical to the ML lifecycle and walk through the development of a semantic search tool for my YouTube videos.
More Resources:
💻 Example Code: https://github.com/ShawhinT/YouTube-B...
🤖 RAG: • How to Improve LLMs with RAG (Overview + P...
📚Text Embeddings: • Text Embeddings, Classification, and Seman...
References:
[1] / software-2-0
[2] https://arxiv.org/abs/2012.07919
Introduction - 0:00
Why ML is Different - 0:39
Role of Experimentation - 3:04
Semantic Search (Design Choices) - 5:09
Example Code: Semantic Search of YT Videos - 8:17
Preview of Final Product - 10:06
Step 1: Experimentation & Evaluation - 11:17
Step 2: Build Video Index - 34:14
Step 3: Build UI - 35:49
What's Next? - 43:43