Lifelines: Survival Analysis in Python

[@przemysawkaleta7815]

6:25 How can this "modern" survival analysis be cooler than actuarial analysis even though it is the same thing?

[@aga5979]

obviously, it is cooler because he is doing it now...teehee...

[@seragsdks]

do you have the code for the survival regression or even slides.

[@callumsmyth3180]

Is the GitHub repo for this still available somewhere?

[@yilingliu358]

wow this guy is so hot. I wish I had my statistical teacher like him back in uni

[@danieljurado7461]

HUGE fan of CDP. What an impact he has made on the data science community and modern business!

[@divyar740]

Thanks a lot :) simple and precise.

[@karannchew2534]

Need to improve typing skill :D

[@anondokolpo]

I was wondering whether this algo can be used for demand forecasting models with capacity peaks

[@tomideadeyeye4002]

Hi Ted Mosby

[@franciscomendoza9766]

im still confused with what duration should be. should it be duration they were in power or duration from start to current_date, since we talk about censorship as well?

[@Arslanqadri]

Francisco Mendoza if end is unknown. Take the time upto the date of analysis.

[@Arslanqadri]

Francisco Mendoza also there is a datetime smtg function in lifelines docs. That saves the trouble

[@sitientibus]

could you please leave that "dd.csv" somewhere? I can only find different versions, I think. Cheers.

[@sitientibus]

Thank you, Samuel! I'll try again!

[@Samuel-se5zw]

import lifelines data = lifelines.datasets.load_dd()

[@Samuel-se5zw]

the dataset is in the lifelines library

[@LukosPC]

Great talk!