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README.md

@@ -1,4 +1,5 @@
 ---
+---
 language: en
 tags:
 - time-series
@@ -16,12 +17,41 @@ metrics:
 
 # 📈 LSTM Stock Price Forecasting
 
-This repository contains an **LSTM model** trained on stock closing prices.  
+This repository contains an **LSTM model** trained on stock closing prices and compared with a traditional ARIMA baseline.  
+The goal is to forecast future stock values and evaluate which approach generalizes better.  
+
+---
+
+## 📊 Dataset
+- **Source:** Yahoo Finance  
+- **Ticker:** Apple Inc. (AAPL)  
+- **Period:** 2015–2023  
+- **Feature Used:** Daily closing price  
+
+---
+
+## 🧠 Models Implemented
+- **ARIMA (Auto ARIMA)** — traditional statistical time-series forecasting  
+- **LSTM** — deep learning recurrent neural network for sequential data  
+
+---
+
+## 📊 Evaluation Results
+
+| Model | RMSE      | MAPE     |
+|-------|-----------|----------|
+| ARIMA | 15.796    | 0.0857   |
+| LSTM  | 7.533     | 0.0397   |
+
+✅ **Conclusion:** LSTM significantly outperforms ARIMA with lower RMSE and MAPE, showing its ability to capture nonlinear patterns in stock prices.
+
+---
+
+## 📈 Example Forecast Plot
+*(You can upload and embed a forecast.png here if available)*  
 
-- Dataset: Yahoo Finance (AAPL, 2015–2023)  
-- Models Compared: ARIMA vs LSTM  
-- Evaluation: RMSE & MAPE using rolling window  
-- Deployment: Hugging Face Hub (`DataSynthis_ML_JobTask`)  
+```markdown
+![Forecast](./forecast.png)
 
 ## Usage
 ```python