StockSense

StockSense is an AI-powered stock trading platform that empowers investors with real-time insights, automated trading, sentiment analysis, and advanced portfolio management. The project is modular, consisting of four main components:

• Frontend: Modern React-based dashboard and UI.
• Backend: FastAPI backend for trading logic, signals, and data APIs.
• Model: Deep learning models for stock price prediction.
• Sentiment Analysis: NLP models for market sentiment from news and social media.

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Table of Contents

• Features
• Project Structure
• Getting Started
• Tech Stack
• License

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Features

• 📈 Stock Price Prediction: ML/DL models for future price forecasting.
• 📰 Sentiment Analysis: Real-time sentiment from news and tweets.
• 🛠️ Automated Trading Signals: Buy/Sell/Neutral recommendations.
• 💼 Portfolio Management: Track and analyze your investments.
• 🌐 Live Market Data: Real-time indices and stock prices.
• 🔒 Authentication: Secure login and signup.
• 🎨 Modern UI: Responsive dashboard with charts and insights.

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Project Structure

StockSense/
├── Backend_StockSense/           # FastAPI backend & trading logic
├── Frontend_StockSense/          # React dashboard & UI
├── Model_StockSense/             # Deep learning models & API
├── Sentiment_Analysis_StockSense/# NLP sentiment analysis & API

• Backend: Backend_StockSense/README.md
• Frontend: Frontend_StockSense/README.md
• Model: Model_StockSense/README.md
• Sentiment Analysis: Sentiment_Analysis_StockSense/README.md

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Getting Started

1. Clone the Repository

git clone https://github.com/yourusername/StockSense.git
cd StockSense

2. Setup Backend

cd Backend_StockSense
python -m venv .venv
.venv\Scripts\activate
pip install -r app/requirements.txt
uvicorn app.main:app --reload --port 8000

3. Setup Model API

cd Model_StockSense
python -m venv venv
venv\Scripts\activate
pip install -r requirements.txt
python src/etl_pipeline.py
python src/model.py --db_path data/stock_data.db --ticker AAPL --epochs 50 --batch_size 32
uvicorn api.main:app --reload --port 8001

4. Setup Sentiment Analysis API

cd Sentiment_Analysis_StockSense
python -m venv venv
venv\Scripts\activate
pip install -r requirements.txt
python src/model.py
uvicorn api.main:app --reload --port 8002

5. Setup Frontend

cd Frontend_StockSense
npm install
npm run dev

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Tech Stack

• Frontend: React, TypeScript, Tailwind CSS, Vite
• Backend: FastAPI, Python
• Model: TensorFlow/Keras, scikit-learn
• Sentiment Analysis: NLTK, scikit-learn, FastAPI
• Database: SQLite (for model training)
• APIs: RESTful endpoints for integration

MAde By ♡ from Team Hackolics(Kanav, Mann, Dhriti, Khushi)