data science

Machine learning models are powerful, but sometimes they produce predictions that break human intuition. Imagine this: you’re predicting house prices. A 2,000 sq. ft. house is predicted cheaper than a 1,500 sq. ft. home. Sounds...

of Shopify, recently told his employees in an internal memo: “Before asking for more headcount and resources, teams must exhibit why they can not get what they need done using AI”. Having worked in...

Certainly one of the essential problems that arises in high-dimensional density estimation is that as our dimension increases, our data becomes more sparse. Due to this fact, for models that depend on local neighborhood...

Learning (ML) model mustn't the training data. As an alternative, it should well from the given training data in order that it could well to latest, unseen data. The default settings...

Paper link: https://arxiv.org/abs/2412.06769 Released: ninth of December 2024 a high concentrate on LLMs with reasoning capabilities, and for a great reason. Reasoning enhances the LLMs’ power to tackle complex issues, fosters stronger generalization, and introduces...

chapter of the in-progress book on linear algebra, “A birds eye view of linear algebra”. The table of contents to date: Stay tuned for future chapters. Here, we'll describe operations we will do with two...

weaving its way into the highlight over the past few years, as organizations try to seek out alternatives to centralized data architectures. I’ve had a front-row seat to observe early adopter teams come to...

discuss how you may perform automatic evaluations using LLM as a judge. LLMs are widely used today for quite a lot of applications. Nonetheless, an often underestimated aspect of LLMs is their use...