Imagine working as a Data Analyst in a healthcare Non-Governmental Organization (NGO) implementing HIV and AIDS programmes across several communities.
The organization has limited resources. There may not be enough funding, healthcare workers, testing kits, transport, outreach teams, or community programmes to serve every community at the same intensity.
This creates an important question:
How can we use data and machine learning to direct limited programme resources to communities with the greatest need?
This is where Machine Learning (ML) can become valuable.
