Continuing my weekend AI experiments with solving last minute childcare needs

Over the weekend, I built a simple proof of concept program in Python using k nearest neighbor classifier to recommend last minute baby sitters based on - 1. Availability Status Classification: Classifying sitters based on their availability patterns (e.g., frequently available, occasionally available, rarely available) using historical data. This can help the system preemptively suggest sitters who are more reliable for last-minute needs and avoid those who are less likely to be available. 2. Suitability Classification: classifying sitters based on additional criteria such as rating, hourly rate, experience level with count of kids, specific age of kids - 0 to 2, 2 to 7, 7 to 12. This helps ensure that not only is the sitter available quickly, but they are also well-suited for the specific circumstances. The python program’s input is the same as needed in any childcare finder website such as care.com - i.e. number of kids, age of each kid, zipcode where childcare is needed, timeslot (start time, end time), hourly rate for the role. Output is a recommendation of a babysitter - name, phone number, rating. Note: since I don’t have access to a database of babysitters, I mimicked a simple sample dataset just for this proof of concept

My Python source code is on my Github: Python/LastminuteChildcareFinder.py at main · AishiMahapatra/Python (github.com)