📰 Towards Data Science

How Knives Out teaches Bayesian thinking (without you realizing it) The post Solving a Murder Mystery Using Bayesian Inference appeared first on Towards Data Sc

Enterprise Document Intelligence [Vol. 1 #2bis] Why stacking a reranker on top of weak retrieval doesn’t save it, what cross-encoders actually fix vs what they

Structure-guided NER optimization for enterprise GraphRAG systems The post Proxy-Pointer RAG: Eliminating Wasteful Entity & Relations Extraction in Knowledge Gr

As AI gets smarter, the real differentiator may be how well humans regulate their own thinking. The post Meta-Cognitive Regulation Might Be the Most Important A

Enterprise Document Intelligence [Vol. 1 #2] Why the same vector search that handles synonyms and paraphrase silently fails on negation, exact identifiers, and

Most engineers see quantization as shrinking vectors. TurboQuant asks a harder question: can you shrink them without breaking their geometry? The post Qdrant Tu

Enterprise Document Intelligence [Vol. 1 #1] The smallest version of RAG that actually works, on a real PDF, with grounded answers and the source lines highligh

Most RAG systems are optimized for answer quality, not cost—and that blind spot gets expensive fast. In this article, I break down a production-ready cost contr

A step-by-step journey from calculus-based optimization to Stochastic Gradient Descent The post Why Gradient Descent Became Stochastic appeared first on Towards

One of the most important concepts in DAX is lineage. It’s about the information on where something comes from. Let’s see what it is and how we can manipulate i

Part 1: A practitioner's walkthrough of univariate, multivariate, covariate-informed, and cold-start forecasting. The post Five Questions About Chronos-2, the T

A retrospective on my MS thesis, the leaderboard it placed on, and the LLM shift that has reshaped the field since. The post EmoNet: Speaker-Aware Transformers

Lessons from building a fast, reliable scientific agent with local open-weight models, vLLM, and long-context infrastructure The post The Infrastructure Behind

And what ORPilot does differently The post Why AI Still Can’t Solve Your Real Mathematical Optimization Problem appeared first on Towards Data Science .

A diffusion-inspired framework for stress-testing and denoising LLM-as-a-Judge pipelines, applied to safety-critical driving video. The post DiffuJudge-AV: A Di

Keep an overview of all your coding agents that run in parallel The post How to Effectively Run Many Claude Code Sessions in Parallel appeared first on Towards

How to Turn Simple Head-to-Head Choices Into Probabilistic Rankings The post Learning From Pairwise Preferences: An Introduction to the Bradley Terry Model appe

Good models don't save bad architecture, and most teams learn that the hard way. The post Most AI Agents Fail in Production Because They’re Built Backwards appe

Why good data work gets ignored after delivery. The post They Requested It. I Built It. Nobody Ever Used It. appeared first on Towards Data Science .

A simple explanation of what a data agent is and how it works The post What Is a Data Agent? appeared first on Towards Data Science .

Why your AI model can be wrong with 99% confidence The post The AI Model Confidence Trap appeared first on Towards Data Science .

How I turned 100 messy pdfs into structured insights by building a deterministic loop around agents The post Stop Using LLMs Like Giant Problem Solvers appeared

How shifting the operational focus from isolated data products to systemic domain architecture resolves technical bottlenecks and optimizes platform investment.

A beginner's honest walkthrough of Extract, Transform, Load using the GitHub API The post I Built My First ETL Pipeline as a Complete Beginner. Here’s How. appe