Silpa - ML Digest

BM25 Made Easy: Visualizing the Core of Modern Search

Imagine you are searching a library for books about “neural networks.” A naive librarian might hand you every book that […]

Imagine a research assistant standing in a library. A standard retrieval-augmented generation (RAG) system gives that assistant a stack of

Imagine that two doctors examine the same patient and both say, “The treatment worked.” One doctor means the fever dropped.

Imagine walking into a library where every book has a helpful librarian attached to it. If you ask about a

Imagine training models the way a research lab might run chemistry experiments. Every run changes something slightly: the learning rate,

Imagine a model that predicts loan defaults. During training, the pipeline pulls account_balance from the warehouse today, but the examples

Imagine hiring a new teammate who can search the web, write code, call APIs, and make decisions without asking for

Imagine trying to deliver a single cup of coffee by sending an entire coffee shop to a customer’s home. That

ONNX (Open Neural Network Exchange) is a standard, open-source format for representing machine learning models as a computation graph. In

In ML, attention is the mechanism that lets a model decide which pieces of information deserve focus at each step.

A production agentic AI system is like a well-run restaurant: success depends not on a single chef or dish, but

Think about your first week at a new job. Every new piece of information lands on a sticky note. By