Deep Dives

To get probably the most out of this tutorial, you need to have already got a solid understanding of how linear regression works and the assumptions behind it. You must also bear in mind...

✨ Overview Traditional machine learning (ML) perception models typically deal with specific features and single modalities, deriving insights solely from natural language, speech, or vision evaluation. Historically, extracting and consolidating information from multiple modalities has...

of this series , , and , we've observed: interpretation of multiplication of a matrix by a vector, the physical meaning of matrix-matrix multiplication, the behavior of several special-type matrices, and visualization of matrix transpose. On this story,...

modeling contexts, the XGBoost algorithm reigns supreme. It provides performance and efficiency gains over other tree-based methods and other boosting implementations. The XGBoost algorithm features a laundry list of hyperparameters, although often only...

: You will have built a fancy LLM application that responds to user queries about a selected domain. You will have spent days organising the entire pipeline, from refining your prompts to adding context...

“stochastic parrots” to AI models winning math contests? While there may be definitely doubt that LLMs are truly PhD-level thinkers as advertised, the progress in complex reasoning situations is undeniable. A popular trick has...

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...

been retained by an insurance company to assist refine home insurance premiums across the southeastern United States. Their query is easy but high stakes: ? They usually don’t just mean , they need...