Update README.md

README.md

@@ -15,14 +15,14 @@ metrics:
 - mape
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-# 📈 LSTM Stock Price Forecasting
+# LSTM Stock Price Forecasting
 
 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.  
 
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-## 📊 Dataset
+## Dataset
 - **Source:** Yahoo Finance  
 - **Ticker:** Apple Inc. (AAPL)  
 - **Period:** 2015–2023  
@@ -30,31 +30,31 @@ The goal is to forecast future stock values and evaluate which approach generali
 
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-## 🧠 Models Implemented
+## Models Implemented
 - **ARIMA (Auto ARIMA)** — traditional statistical time-series forecasting  
 - **LSTM** — deep learning recurrent neural network for sequential data  
 
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-## 📊 Evaluation Results
+## 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.
+**Conclusion:** LSTM significantly outperforms ARIMA with lower RMSE and MAPE, showing its ability to capture nonlinear patterns in stock prices.
 
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-## 📈 Example Forecast Plot
+## Example Forecast Plot
 
 Below is an example forecast visualization (LSTM predictions vs actual stock prices):
 
 ![Forecast Example](./forecast.png)
 
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-## 📊 ARIMA vs LSTM Forecasts
+## ARIMA vs LSTM Forecasts
 
 **ARIMA Forecast:**
 ![ARIMA](./forecast_arima.png)
@@ -62,14 +62,14 @@ Below is an example forecast visualization (LSTM predictions vs actual stock pri
 **LSTM Forecast:**
 ![LSTM](./forecast.png)
 
-## 🚀 Deployment
+## Deployment
 - Model hosted on **Hugging Face Hub**  
 - Repository: `Jalal10/DataSynthis_ML_JobTask`  
 - Includes model weights (`lstm_stock_model.h5`) and usage instructions  
 
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-## 💻 Usage
+## Usage
 
 ```python
 from huggingface_hub import hf_hub_download