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README.md

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+# 📈 Stock Price Forecasting – ARIMA & LSTM  
+
+This project demonstrates **time-series forecasting** on stock prices using both:  
+- **ARIMA** (classical statistical model)  
+- **LSTM** (deep learning model)  
+
+The app is deployed with **Gradio on Hugging Face Spaces** so you can upload stock price data and generate **future forecasts interactively**.  
+
+---
+
+## 🚀 Features
+✅ Upload your own stock CSV (must include a **`Close`** column).  
+✅ Forecast with **ARIMA**, **LSTM**, or **Compare Both**.  
+✅ Interactive **forecast horizon slider (5–30 days)**.  
+✅ **Forecasted table** + **visual chart** output.  
+✅ Clean, modular code for easy extension.  
+
+---
+
+## 🧠 Models Used
+- **ARIMA** (`arima.pkl`)  
+  - Captures autocorrelation and seasonality in time series.  
+- **LSTM** (`lstm.pth`)  
+  - Learns nonlinear sequential dependencies in stock prices.  
+
+Both models are pre-trained and loaded inside the app.  
+
+---
+
+## 📂 Project Structure
+```
+
+├── app.py            # Main Gradio app
+├── arima.pkl         # Saved ARIMA model
+├── lstm.pth          # Trained LSTM model
+├── requirements.txt  # Dependencies
+└── README.md         # Documentation
+
+````
+
+---
+
+## 📊 Input Format
+Upload a **CSV file** with at least one column:  
+
+| Date       | Open   | High   | Low    | Close   | Volume  |
+|------------|--------|--------|--------|---------|---------|
+| 2024-01-01 | 100.25 | 101.20 | 99.80  | 100.90  | 2000000 |
+| 2024-01-02 | 100.90 | 102.10 | 100.30 | 101.70  | 1800000 |
+| ...        | ...    | ...    | ...    | ...     | ...     |
+
+Only the **`Close`** column is required.  
+
+---
+
+## ⚙️ Installation & Run Locally
+Clone this repo and install dependencies:
+```bash
+git clone https://huggingface.co/spaces/mrshibly/DataSynthis_ML_JobTask
+cd DataSynthis_ML_JobTask
+pip install -r requirements.txt
+````
+
+Run the app locally:
+
+```bash
+python app.py
+```
+
+The app will run on: [http://localhost:7860](http://localhost:7860)
+
+---
+
+## 🌐 Deployment on Hugging Face Spaces
+
+This project is ready to run on **Hugging Face Spaces (Gradio)**.
+
+* Upload `app.py`, `arima.pkl`, `lstm.pth`, `requirements.txt`, and `README.md`.
+* Hugging Face will automatically detect `app.py` and launch the Gradio app.
+
+---
+
+## 📈 Example Output
+
+**Forecast Horizon: 10 days, Compare Both**
+
+* **Forecast Table**
+  | Future | ARIMA Forecast | LSTM Forecast |
+  |--------|----------------|---------------|
+  | t+1    | 101.2          | 101.5         |
+  | t+2    | 101.4          | 102.1         |
+  | ...    | ...            | ...           |
+
+* **Forecast Plot**
+  Historical data (blue) + Predictions (orange/green).
+
+---
+
+## 💡 Why This Project is Interesting
+
+* Combines **traditional stats** and **modern deep learning** in one tool.
+* Clear comparison of model performance for real-world time series.
+* Deployed in an interactive way → **turns research into a product**.
+
+---
+
+## 👨‍💻 Author
+
+Developed by **[Md. Mahmudur Rahman]**
+*Built as part of a job interview task – demonstrating forecasting, ML/DL, and deployment skills.*
+
 ---
 title: DataSynthis ML JobTask
 emoji: 🐨