Building a PCA and SVD-Based Development Analytics System Using World Bank Data

1. 1Collect World Bank data on various development indicators
2. 2Apply Principal Component Analysis (PCA) to reduce data dimensionality
3. 3Use Singular Value Decomposition (SVD) to identify underlying patterns
4. 4Visualize the results to gain insights into development trends
5. 5Refine the model by iterating on the data and methods

Data scientists and analysts on a team can benefit from this micro-lesson to improve their development analytics skills, and product managers can use this insight to inform product development

💡 PCA and SVD can help uncover hidden patterns in development data, providing a more nuanced view of a country's development

📊 Use PCA & SVD to uncover development trends beyond GDP #datascience #developmentanalytics