Update README.md

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: 🐨