Data Science & Machine Learning Portfolio

This repository contains a collection of data science, machine learning, and web development projects organized in a standard structure.

Repository Structure

├── projects/
│   ├── data-science/        # Data science and ML projects
│   ├── web-apps/           # Web applications and frontend projects
│   ├── algorithms/         # Algorithm implementations and practice
│   └── competitions/       # Coding competitions and hackathons
├── notebooks/
│   ├── courses/           # Educational notebooks from courses
│   └── exploratory/       # Experimental and research notebooks
├── datasets/              # Data files and datasets
├── docs/                  # Documentation
└── scripts/              # Utility scripts

Technologies Used

• Python: Data science, machine learning, algorithms
• JavaScript/React: Web applications and frontend development
• Jupyter Notebooks: Data analysis and experimentation
• Flask: Web backend development
• PyTorch/TensorFlow: Deep learning frameworks
• Apache Airflow: Data pipeline orchestration

Getting Started

Each project contains its own README with specific setup instructions. Most Python projects require:

pip install -r requirements.txt

For React projects:

npm install
npm start

Important Security Notice for Web Applications

myflaskapp (projects/web-apps/myflaskapp)

The applications within the myflaskapp directory require access to the Upstox API. Environment variables are used for secure credential management.

Required Environment Variables:

• client_id: Your Upstox API client ID
• client_secret: Your Upstox API client secret
• BUCKET: Google Cloud Storage bucket name
• UPSTOX_AUTH_CODE: Temporary authorization code from Upstox OAuth flow
• UPSTOX_REDIRECT_URI: OAuth redirect URI

poisonous_mushrooms (projects/data-science/poisonous_mushrooms)

The Streamlit application connects to a FastAPI prediction service.

Required Environment Variable:

• PREDICTION_API_URL: Full URL to the prediction API endpoint

Security Best Practices:

• Never commit .env files or hardcode credentials
• Use environment variables for all sensitive configuration
• Rotate API keys and tokens regularly