COCA‑COLA STOCK PREDICTOR

01 — The Problem

"Stock prediction is notorious for being inaccurate. Can we reliably forecast blue-chip stability using classic ML indicators?"

02 — Overview

A data science project that analyzes and predicts Coca-Cola stock prices using Python and machine learning. It encompasses end-to-end data cleaning, exploratory visualizations, and the calculation of technical indicators. The pipeline compares multiple Scikit-learn regressors, evaluating them with strict metrics, and includes live data updates for real-time forecasting.

03 — Drawbacks & Future Scope

It currently struggles with sudden market crashes—because black swan events are notoriously hard to bottle. Adding financial sentiment analysis will give it a better taste of market volatility.