Welcome to the Global Aid Insight repository, a pioneering initiative that combines the prowess of Hierarchical Clustering and Principal Component Analysis (PCA) to offer a visionary solution. Our mission is to empower decision-makers, like CEOs, with data-driven insights that facilitate strategic support for countries in need.
Introduction: Global Aid Insight is a transformative project designed to identify clusters among country data, guiding impactful interventions for sustainable development. By harnessing the power of Hierarchical Clustering and PCA, we uncover hidden patterns within complex datasets to enable informed decisions.
Features:
Hierarchical Clustering: Our project employs Hierarchical Clustering to classify countries into distinct groups based on similarities. This technique unveils underlying relationships among countries, paving the way for targeted assistance.
Principal Component Analysis (PCA): Embracing the magic of PCA, we reduce the dimensionality of the data while retaining its essence. This aids in simplifying complex data structures and highlighting dominant trends, assisting decision-makers in discerning critical factors.
Strategic Insights: The clustering outcomes and PCA-derived insights collectively furnish CEOs and decision-makers with a comprehensive understanding of countries' needs, fostering data-backed strategies for efficient resource allocation.