Model Explainability: Making Sense of SHAP and LIME
Your model just denied someone a loan, flagged a tumour, or rejected a job application — and when the person asks …
Abhay
5 min read
Your model just denied someone a loan, flagged a tumour, or rejected a job application — and when the person asks …
Abhay
5 min read
A neural network is, at heart, a very confident guesser that is wrong a lot at first. You show it a photo of a cat, it …
Abhay
4 min read
There’s an old saying that you’re the average of the five people you spend the most time with. k-Nearest …
Abhay
4 min read
Let’s clear up the worst-named algorithm in machine learning right away: logistic regression does classification, …
Abhay
4 min read
There’s a student we all remember from school: the one who memorised every answer in the textbook, aced the …
Abhay
4 min read
Imagine stacking ten layers of neurons, training for hours, burning through GPU credits — and ending up with something …
Abhay
4 min read
There’s a seductive myth in machine learning: that the path to a better model runs through a fancier algorithm. …
Abhay
5 min read
You already know what a learning rate is: the size of the step your model takes downhill each time it learns. What …
Abhay
4 min read
Imagine handing a stack of photos to two assistants. The first one gets a tidy answer key: “this is a cat, this is …
Abhay
5 min read
Strip away the hype and almost every machine learning model — from a humble linear regression to a 70-billion-parameter …
Abhay
4 min read