Uber Nairobi Ambulance Perambulation Challenge
$6,000 USD
Can you use ML to create an optimised ambulance deployment strategy in Nairobi?
562 data scientists enrolled, 152 on the leaderboard
17 September—24 January 2021
Ends in 3 months
Did anyone try clustering?
published 6 Oct 2020, 10:35

Kind of baseline approach to just cluster the crash location and check if most of the accidents happen around 6 hotspot?

yes i tried it quickly with no tuning, and it did get me on to 50 score (in 5/10/2020), but normal grediant desent did better job and get me to 40 score

cool, same experience. Will try after adding in the other data points

how did you write the code for generating the sample submission. abit stuck on that.

you have to predict the six positions for each 3 hour window in the submission file. Just replace the coordinates in the provided sample submission file.

Yes, me too , got a result of 51. will try normal gradient descent now.

Hi! :) Was wondering, how do you use gradient descent to tackle this challenge?