A modern, responsive portfolio website built with React, TypeScript, and Tailwind CSS to showcase data science projects and skills.
- Responsive design with Tailwind CSS
- Interactive data visualizations using Recharts
- Smooth animations with Framer Motion
- Type-safe development with TypeScript
- Fast development and build process with Vite
- React 18
- TypeScript
- Tailwind CSS
- Vite
- React Router DOM
- Framer Motion
- Recharts
- Lucide React (for icons)
- Clone the repository
git clone <https://github.com/prathamesh693/My_Portfolio>
2. Run the development server
```bash
npm run dev
## Project Structure
```bash
├── public/
│ ├── index.html
│ └── ...
├── src/
│ ├── assets/
│ │ ├── images/
│ │ └── ...
│ ├── components/
│ │ ├── About/
│ │ ├── Contact/
│ │ ├── Footer/
│ │ ├── Header/
│ │ ├── Hero/
│ │ ├── Layout/
│ │ ├── Projects/
│ │ └──...
│ ├── pages/
│ │ ├── About/
│ │ ├── Contact/
│ │ ├── Home/
│ │ └──...
│ ├── App.tsx
│ ├── index.css
│ ├── main.tsx
│ └──...
├── package.json
├── tailwind.config.js
├── tsconfig.json
└── vite.config.ts- About Section: Provides an overview of the portfolio owner's background, skills, and interests.
- Projects Section: Displays a collection of data science projects with descriptions, technologies used, and links to live demos or GitHub repositories.
- Contact Section: Allows visitors to get in touch with the portfolio owner through a contact form or other communication channels.
- Credit Card Fraud Detection
- Anomaly Detection using machine learning techniques.
- Python, scikit-learn, pandas, matplotlib, seaborn.
- Telecom Customer Churn Prediction
- Customer churn analysis and prediction using advanced machine learning algorithms.
- Technologies: Python, Pandas, NumPy, scikit-learn, XGBoost, Matplotlib, Seaborn, Plotly, Joblib, Streamlit
- Interactive data visualization and model deployment
