A project for learning data processing, machine learning, and visualization. This platform allows users to clean data, apply machine learning models, and visualize results interactively.
- Data Preprocessing: Handle missing values, scale features, and explore data.
- Machine Learning: Train simple models for prediction, clustering, and anomaly detection.
- Visualization: Create interactive dashboards with data insights.
- API Integration: Use Flask or FastAPI to expose ML predictions.
- Deployment: Dockerized services deployed on Heroku or cloud providers.
- Requirements Gathering and Research: Understand ML basics and gather datasets.
- Data Collection and Preprocessing: Clean and prepare data for analysis.
- Data Visualization: Build static and interactive charts.
- ML Model Training and Evaluation: Train models and evaluate performance.
- Backend Development: Create APIs for predictions and data uploads.
- Frontend Dashboard: Develop a user-friendly interface.
- Deployment: Deploy services using Docker and cloud tools.
- Testing and Documentation: Ensure quality and write detailed guides.
- Python 3.8+
- pip (Python package installer)
- Git
- Docker (optional for deployment)
- Clone the repository:
git clone https://github.com/your-username/ML-Data-Insights-Project.git cd ML-Data-Insights-Project
