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https://github.com/adilshamim8/stock_price_prediction

A simple LSTM-based machine learning project to predict stock prices using historical data.
https://github.com/adilshamim8/stock_price_prediction

datascience deeplearning finance lstm neuralnetworks python stockprediction tensorflow timeseriesanalysis

Last synced: 3 months ago
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A simple LSTM-based machine learning project to predict stock prices using historical data.

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README

          

# Stock Price Prediction – Predict the Future, Today.

Welcome to a project built with curiosity, passion, and a love for learning.
This is not just code — it’s a step toward understanding how data and AI can help us see patterns in the stock market.

The model predicts stock prices and shows them compared to actual values on a graph.
![Output](OutPut.gif)

## What This Project Is About

This project uses **machine learning** (LSTM model) to predict stock prices based on historical data.

It takes real stock data, processes it, trains a deep learning model, and then makes predictions.
If you’re new to ML or just curious about the stock market, this is a great place to start.

---

## What You’ll Learn

- How to collect stock data using Yahoo Finance
- How to clean and prepare time-series data
- How LSTM (a type of neural network) works for prediction
- How to visualize stock price predictions vs real prices

---

## Tools & Libraries Used

- Python
- Pandas & NumPy
- Matplotlib
- Scikit-learn
- TensorFlow / Keras
- yfinance (Yahoo Finance API)

---

## How to Run It

1. Clone the repo:
```bash
git clone https://github.com/AdilShamim8/Stock_Price_Prediction.git
cd Stock_Price_Prediction
```

2. Install the required libraries:

```bash
pip install -r requirements.txt
```

3. Run the project:

```bash
python main.py
```
---

### Want to Contribute?

Feel free to fork this repo, play with the code, and improve it.
Pull requests and suggestions are always welcome!

### Connect With Me

**Made by Adil Shamim**
Let’s connect and build cool things together.

* LinkedIn: [adilshamim8](https://www.linkedin.com/in/adilshamim8)
* Kaggle: [adilshamim8](https://www.kaggle.com/adilshamim8)
* X: [adil_shamim8](https://x.com/adil_shamim8)