# 📈 NSE Stock Predictor

A web-based stock price prediction application built using Streamlit that predicts NSE stock prices using Machine Learning (KNN), Deep Learning (LSTM), and News Sentiment Analysis.

---

## 🧠 Project Overview

This application fetches historical NSE stock data, applies feature engineering, predicts future stock prices using KNN and LSTM models, analyzes recent financial news sentiment, and visualizes everything through interactive charts.

---

## 🚀 Features

- Real-time NSE stock data fetching  
- Stock price prediction for upcoming days  
- Machine Learning model (K-Nearest Neighbors)  
- Deep Learning model (LSTM Neural Network)  
- News-based sentiment analysis  
- Interactive candlestick and prediction charts  
- Modern dark-themed UI using Streamlit  

---

## 🛠️ Tech Stack

- Programming Language: Python  
- UI Framework: Streamlit  
- Data Processing: Pandas, NumPy  
- Visualization: Plotly  
- Machine Learning: Scikit-learn  
- Deep Learning: TensorFlow (Keras)  
- NLP: NLTK (VADER Sentiment Analyzer)  
- Data Source: NSE Python API  

---

## ⚙️ How It Works

1. User enters an NSE stock symbol (example: TCS)
2. Historical stock data is fetched from NSE
3. Technical features such as lag values and moving averages are created
4. KNN and LSTM models predict future stock prices
5. Recent news headlines are analyzed for sentiment
6. Results are displayed using charts and performance metrics

---

## ▶️ How to Run the Project

### 1. Clone the Repository
```bash
git clone https://github.com/your-username/nse-stock-predictor.git
cd nse-stock-predictor