RAG: How to Use Standard Deviation and Z-Scores to Predict the Future

This tutorial demonstrates how to build a RAG (Retrieval-Augmented Generation) application that functions as a simple financial advisor using Bollinger Z-scores to guide stock investment decisions. Learn to implement a system that analyzes whether to invest in stocks by leveraging LangGraph, OpenAI models, and Yahoo Finance data. The 48-minute video walks through creating a financial advisor that uses statistical concepts like standard deviation and Z-scores for predictive analysis in stock markets. Access the complete implementation through the provided GitHub notebook to enhance your machine learning and data science skills in financial applications.