The Confusion Matrix: Precision, Recall, and F1 Made Simple
Imagine you build a model to detect a rare disease that shows up in 1% of patients. You hit the green button, and your …
Abhay
4 min read
Imagine you build a model to detect a rare disease that shows up in 1% of patients. You hit the green button, and your …
Abhay
4 min read
There is a machine learning algorithm that makes an assumption so wrong it has the word “naive” baked right …
Abhay
4 min read
Picture this: you build a fraud detector, run it on a million transactions, and it scores a glorious 99.8% accuracy. You …
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
A language model is brilliant at language and hopeless at facts that aren’t in its head. Ask it today’s …
Abhay
4 min read
Imagine a dataset with a thousand columns. Customer records, gene expression levels, pixel intensities — pick your …
Abhay
5 min read
Full fine-tuning a large language model is a bit like repainting your entire house because you wanted the bathroom door …
Abhay
4 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
Large language models are dazzling conversationalists with the long-term memory of a goldfish. Ask one about your …
Abhay
4 min read