5 interesting things (26/06/2019)

Checklist for debugging neural networks – well written trouble shooting for neural networks models which is not language or framework specific!
https://towardsdatascience.com/checklist-for-debugging-neural-networks-d8b2a9434f21

Why Software Projects Take Longer Than You Think A Statistical Model – great post about a problem we all face. Usually we try to solve it using “instrumental changes” – changing methods \ processes \ … . This post tries to show that there is more to it than just the behavioural change.

Google What-If-Tool (WIT) – A nice tool by Google that was released few month ago. The terminology is actually a bit misleading and counterfactuals don’t carry the meaning they have in causal inference. It is more like matching with two possible distance matrices – L1 and L2.

causallib – New python causal inference package from IBM
There is also a python causal inference package from Microsoft which was released about a year ago – https://github.com/Microsoft/dowhy.

A Visual Intro to NumPy and Data Representation – What can I say, I really like Jay’s guides –
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