Machine learning made me rethink a small assumption in Nairobi

Tola Ibrahim · 66 likes

That is a surprisingly elegant way to frame it. The social part surprised me too. This is exactly the kind of tradeoff teams argue about for weeks

Avery Johnson · 20 likes

glad you shared it; small wins count. The low-effort version is probably teh keeper

[deleted] · 4 likes

Can you expand on that a bit?

Rapid Comet · 18 likes

you explained the tradeoff realy clearly. The the train station detail changes the whole answer. Naming things remains undefeated as the hardest problem

Aarav Sharma · 16 likes

There is a hidden assumption here that not everyone shares. It sounds small, but the practice run matters

Ananya Rao · 12 likes

I love this. It feels practical without pretending life is neat. The Dublin example makes it feel concrete

Grace Parker · 4 likes

you explained the tradeoff really clearly. Honestly, the simplest version wins for me. A small test case would make this easier to trust

Giulia Rossi · 3 likes

what happened after the first week? I am curious whether learning stayed easy

Maksym Bondar · 1 likes

That is a good boundary

Gentle Rider · 0 likes

Kind of wild how often happened is the whole issue

Priya Nair · 2 likes

I appreciate the honest middle stage, not just the polished ending. The Toronto example makes it feel concrete

Sara Ahmed · 1 likes

Beautifully put. I needed that reminder today. That is the kind of detail beginners miss

Tola Ibrahim · 0 likes

Amazing how much difference one small change can make. The low-effort version is probably the keeper

Chloe Davis · 0 likes

I am curious what changed your mind