Learning

part in a two-part series on career-long learning as a knowledge scientist. The primary article covered why try to be a career-long learner and the right way to give you topics to review. In...

was co-authored by Sebastian Humberg and Morris Stallmann. Introduction      Machine learning (ML) models are designed to make accurate predictions based on patterns in historical data. But what if these patterns change overnight? For...

that frustrating hovering drone from ? The one which learned to descend toward the platform, go through it, after which just… hang around below it eternally? Yeah, me too. I spent a whole afternoon...

use gradient descent to seek out the optimal values of their weights. Linear regression, logistic regression, neural networks, and enormous language models all depend on this principle. Within the previous articles, we used...

, we'll implement AUC in Excel. AUC is normally used for classification tasks as a performance metric. But we start with a confusion matrix, because that's where everyone begins in practice. Then we'll see why a...

confusing questions in tech straight away is: Each are six-figure jobs, but when you select the flawed one, you can waste months of your profession learning the flawed skills and miss out on quality...

“The event of mathematics toward greater precision has led, as is well-known, to the formalization of enormous tracts of it, in order that one can prove any theorem using nothing but a couple of...

(NLP) revolutionized how we interact with technology. Do you remember when chatbots first appeared and appeared like robots? Thankfully, that’s prior to now! Transformer models have waved their magic wand and reshaped NLP tasks....