S L Happy - ML Digest

How k-Nearest Neighbors (KNN) Works: From Geometric Intuition to Algorithms

There is an old proverb that perfectly captures the intuition behind one of the most fundamental algorithms in machine learning: […]

1. The Intuition: The Overconfident Weather Forecaster Imagine planning a weekend picnic. You check two weather applications. You cancel the

Fraud detection for payments is a real-time decision problem under uncertainty:you must decide to approve, decline, or step-up a payment

Guardrails are the technical and operational controls that reduce the chance an LLM system causes harm, violates policy, leaks sensitive

Imagine you are a real estate agent. A client walks in and asks: “How much should I list my house

1. Problem framing (what “reactive RCA” means) Imagine you are a doctor in a busy emergency room. A patient (the

Imagine you are in a kitchen trying to cook a new, complex dish. You do not just grab random ingredients

Perplexity answers one narrow question: When the true next token is revealed, how confused/uncertain is the model? It is a

BART is a sequence-to-sequence (encoder–decoder) Transformer pretrained as a denoising autoencoder: it learns to reconstruct clean text $x$ from a

RLHF is a post-training recipe for turning a broadly capable language model into a more useful assistant. In practice, it

Think of BERT as a strong, general-purpose “reader” that turns text into contextual vectors. The moment you move from a

Chatbots produce text. Agents produce outcomes. The conceptual shift is simple: instead of stopping at an answer, an AI agent