Create README.md

README.md

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+#  DataSynthis_ML_JobTask
+
+##  Task Overview
+This project focuses on **Time-Series Forecasting of Stock Prices**.  
+We used historical stock data to forecast future closing prices.
+
+##  Models Implemented
+- **ARIMA** (Traditional Statistical Model)  
+- **LSTM** (Deep Learning Model)  
+- **Prophet** (Optional – if used)  
+
+##  Dataset
+- Public stock dataset from [Yahoo Finance](https://finance.yahoo.com/).  
+- Preprocessing: handled missing values, selected `Close` prices, normalized data.  
+
+##  Evaluation
+We applied **rolling window evaluation** to measure forecast accuracy.  
+
+### Performance Comparison
+
+| Model    | RMSE   | MAPE   |
+|----------|--------|--------|
+| ARIMA    | X.XX   | X.XX%  |
+| LSTM     | X.XX   | X.XX%  |
+| Prophet  | X.XX   | X.XX%  |
+
+*(Replace `X.XX` with your results)*
+
+##  Results & Recommendation
+- **LSTM** generalized better, capturing long-term patterns.  
+- **ARIMA** worked for short-term stable data.  
+- **Prophet** was useful for trend/seasonality but less accurate than LSTM.  
+
+**Final Recommendation:** Use **LSTM** for stock forecasting.  
+
+## Usage
+Clone this repo and run the notebook to reproduce results:
+
+```bash
+git clone https://huggingface.co/amlucky/DataSynthis_ML_JobTask
+
+##  License
+MIT License