How Knives Out teaches Bayesian thinking (without you realizing it)
The post Solving a Murder Mystery Using Bayesian Inference appeared first on Towards Data Science.
Rerankers Aren’t Magic Either: When the Cross-Encoder Layer Is Worth the Cost
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 don’t, and where the editorial position of the series lands.
The post Rerankers Aren’t Magic Either: When the Cross-Encoder Layer Is Worth t...
Meta-Cognitive Regulation Might Be the Most Important AI Skill Nobody Is Talking About
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 AI Skill Nobody Is Talking About appeared first on Towards Data Science.
Embeddings Aren’t Magic: The Predictable Failure Modes of RAG Retrieval
Enterprise Document Intelligence [Vol. 1 #2] Why the same vector search that handles synonyms and paraphrase silently fails on negation, exact identifiers, and your company’s acronyms, and what to use when it does.
The post Embeddings Aren’t Magic: The Predictable Failure Modes of RAG Retrieval appe...
Qdrant TurboQuant Explained: Is TurboQuant the Silver Bullet?
Most engineers see quantization as shrinking vectors. TurboQuant asks a harder question: can you shrink them without breaking their geometry?
The post Qdrant TurboQuant Explained: Is TurboQuant the Silver Bullet? appeared first on Towards Data Science.
Baseline Enterprise RAG, From PDF to Highlighted Answer
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 highlighted.
The post Baseline Enterprise RAG, From PDF to Highlighted Answer appeared first on Towards Data Science.
A step-by-step journey from calculus-based optimization to Stochastic Gradient Descent
The post Why Gradient Descent Became Stochastic appeared first on Towards Data Science.
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 it.
The post Explaining Lineage in DAX appeared first on Towards Data Science.
Why AI Still Can’t Solve Your Real Mathematical Optimization Problem
And what ORPilot does differently
The post Why AI Still Can’t Solve Your Real Mathematical Optimization Problem appeared first on Towards Data Science.
How to Effectively Run Many Claude Code Sessions in Parallel
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 Data Science.
What a recent study on ChatGPT, Python, R, and Stata tells us about AI-assisted coding for causal inference
The post Can AI Write Your Code? appeared first on Towards Data Science.
The Ultimate Beginners’ Guide to Building an AI Agent in Python
Simple step-by-step tutorial to building an AI agent in Python
The post The Ultimate Beginners’ Guide to Building an AI Agent in Python appeared first on Towards Data Science.
Beyond the Model: Why Data Scientists Must Embrace APIs and API Documentation
Unlock the power of API for data-driven solutions
The post Beyond the Model: Why Data Scientists Must Embrace APIs and API Documentation appeared first on Towards Data Science.
How to Mathematically Choose the Optimal Bins for Your Histogram
Optimal Resolution in Histograms: A Rigorous Bayesian Approach to Density Fitting
The post How to Mathematically Choose the Optimal Bins for Your Histogram appeared first on Towards Data Science.
Lost in Translation: How AI Exposes the Rift Between Law and Logic
The tension between Legal and IT has always been frustrating but AI is about to make it worse, at scale. The answer is observable compliance: encoding legal intent directly into architecture.
The post Lost in Translation: How AI Exposes the Rift Between Law and Logic appeared first on Towards Data ...
3 Claude Skills Every Data Scientist Needs in 2026
If you don't want to be left behind, start doing these things with Claude
The post 3 Claude Skills Every Data Scientist Needs in 2026 appeared first on Towards Data Science.
Benders’ Decomposition 101: How to Crack Open a Stochastic Program That’s Too Big to Swallow Whole
Whenever you can rewrite an optimization problem so that fixing some variables makes the rest separable, you could try Benders.
The post Benders’ Decomposition 101: How to Crack Open a Stochastic Program That’s Too Big to Swallow Whole appeared first on Towards Data Science.
Proxy-Pointer RAG: Solving Entity and Relationship Sprawl in Large Knowledge Graphs
A scalable semantic localization layer for entity and relationship reconciliation
The post Proxy-Pointer RAG: Solving Entity and Relationship Sprawl in Large Knowledge Graphs appeared first on Towards Data Science.