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Data Science & Analysis

Data Science, Analysis & Programming

Rochelle is an eco-quant specialized in developing quantitative and qualitative impact methodologies, data visualization, and applying machine learning to ESG (environmental, social and governance) analysis. More data to come…


Cluster analysis for indicator for undernourishment, maternal mortality rate and access to internet use vs. ICT development for 83 countries (from left to right)

Cluster analysis for indicator for undernourishment, maternal mortality rate and access to internet use vs. ICT development for 83 countries (from left to right)

Measuring the effect of ICT indicators on sustainable development indicators using regression and cluster analysis 

Building off Rochelle's work for Huawei's ICT Sustainable Development Goals Benchmark, Rochelle gathered data from the Sustainable Development Solutions Network, ITU and the World Bank to test the relationship between ICT (information communications technology) performance and sustainable development of 83 countries.

She ran a linear regression, and then Lasso and Ridge regressions to isolate relevant features. These features she then used in a cluster analysis, an unsupervised machine learning technique, to determine if there were similarities among  countries.  

She found that health-related sustainable development indicators are most correlated with ICT development, suggesting an area where ICT investment has proven successful for health outcomes historically and should continue to be focused to further benefit health-related outcomes, particularly in developing countries. 

Full presentation and Python notebook can be accessed on Github.