This analysis system is a comprehensive data-driven platform built using Python, Dash, and Plotly to explore and visualize key tech investment insights, using the dataset provided by RunQL. The system allows users to analyze investment trends, funding stages, investor demographics, and regional patterns through interactive dashboards.
Additionally, a prediction model powered by Scikit-Learn forecasts sector trends in 2025, helping users make informed financial decisions based on historical data.
- Interactive Dashboards: Built with Dash & Plotly, allowing dynamic exploration of investment trends.
- Investment Trends Analysis: Insights into funding stages, investor demographics, and regional investment patterns.
- Predictive Modeling: Uses Scikit-Learn to forecast future sector trends with machine learning (random forest classification and regression).
- Data-Driven Decision Making: Enhances strategic investment choices by leveraging historical data and analytics.
- Python (Core programming language)
- Dash & Plotly (For interactive data visualization)
- Scikit-Learn (For machine learning-based predictions)
- Pandas & NumPy (For data processing and analysis)
- CxC 2025 Data Hackathon, powered by Federato
- Based on BriefedIn Dataset by RunQL
- Project by MingMing Z, Katherine C, Deepika A, Chandni W.