Estimating from No Data: Deriving a Continuous Score from Categories | Towards Data Science
Towards Data Science - Mediumby Elod Pal Csirmaz·21 Aug 2026
It has proven trivial to train a neural net to predict one of the three outcomes from the 8 features with almost complete accuracy.
Retrieve One Row from a Table, Not the Whole Table: Row-Level Chunks for RAG | Towards Data Science
Towards Data Science - Mediumby Kezhan Shi·21 Aug 2026
This article is part of Part II of Enterprise Document Intelligence, a series that builds an enterprise RAG system from four bricks.
The Types of Dimensions in a Star Schema, and How to Use Them | Towards Data Science
Towards Data Science - Mediumby Salvatore Cagliari·21 Aug 2026
A short Intro to Dimensional modelling To begin, here is a short introduction to what a Star Schema is and what dimensional modelling is.
Bayesian Guardrails for AI Decisions: Measuring Uncertainty Before Automating Decisions | Towards Data Science
Towards Data Science - Mediumby Mahe Jabeen Abdul·21 Aug 2026
Most AI systems in production are optimized to provide an answer. This format can make the model seem more certain than it actually is.
How Benders Decomposition Works, Part II: Feasibility Cuts | Towards Data Science
Towards Data Science - Mediumby Luis Fernando Pérez Armas·21 Aug 2026
That value allowed us to generate an optimality cut. The subproblem effectively told the master that its decision was feasible, but that operating under it would cost more than expected.
How to Effectively Align Your Intent with Claude Code | Towards Data Science
Towards Data Science - Mediumby Eivind Kjosbakken·20 Aug 2026
There are numerous bottlenecks that I’ve experienced now that coding has become commoditized and we can write more code a lot faster with Claude Code and Codex.
The LLM Judge That Kept Agreeing With Itself | Towards Data Science
Towards Data Science - Mediumby Priyansh Bhardwaj·20 Aug 2026
For a few weeks it worked well enough that we stopped watching it closely. Then a query that should have been flagged got approved and ran.
Three Kinds of RAG Corpus, and What It Costs to Build for the Wrong One | Towards Data Science
Towards Data Science - Mediumby angela shi·20 Aug 2026
On a demo folder that works. On an enterprise shelf it stops working, and not because a parameter is set wrong.
How to Fine-Tune an LLM: An End-to-End Guide | Towards Data Science
Towards Data Science - Mediumby Sam Black·20 Aug 2026
Why fine-tune ? Let me provide a real, personal example. We fine-tuned a 7B parameter model which completely blows foundation models out of the water, but just for this very narrow subtask: Filling...
Making the Knowledge Layer a Graph You Actually Traverse | Towards Data Science
Towards Data Science - Mediumby Miodrag Cekikj·20 Aug 2026
The architecture held up. The contradiction register refused to answer a question the firm itself had not settled.
How to Scale an Integration Pipeline Without Breaking Correctness | Towards Data Science
Towards Data Science - Mediumby Yuelin Ou·19 Aug 2026
I went back and forth for a while on whether to It sounds simple. System A calls system B’s API, what’s the big deal.
Understanding Anti-AI Public Opinion | Towards Data Science
Towards Data Science - Mediumby Stephanie Kirmer·19 Aug 2026
Many journalists and politicians are looking for a single factor to explain this pattern. Is it the power bills? AI slop taking over our social media feeds? The irritating noise data centers make?
Jigsaw Jeeves: Building a Puzzle Assistant using Computer Vision | Towards Data Science
Towards Data Science - Mediumby Chinmay Kakatkar·19 Aug 2026
The puzzle itself is not the issue. After all, you sat down to solve the puzzle because you enjoy the intellectual challenge.
From Prototype to Production: The Architecture Behind Secure & Governed AI Agents | Towards Data Science
Towards Data Science - Mediumby Partha Sarkar·18 Aug 2026
A There are several reasons for this, primary among them being infra and data readiness, but also building responsible AI — model & agent governance, security, transparency, explainability, etc.
Building Enterprise Agent Systems that People can Trust, Verify and Improve | Towards Data Science
Towards Data Science - Mediumby Sheila Teo·18 Aug 2026
I I’ve distilled my experience into 5 principles for building agent systems that succeed inside a business, earn people’s trust and improve over time.
Graph Engineering Isn’t About More Connections — It’s About Which Ones Get Used | Towards Data Science
Towards Data Science - Mediumby Emmimal P Alexander·18 Aug 2026
TL;DR What I did: built a controlled experiment that isolates one variable, relationship density, from everything usually confounded with it, using a fully deterministic agent policy instead of...
Ten Is Not a Hundred | Towards Data Science
Towards Data Science - Mediumby Javier Marin·18 Aug 2026
The problem If you review it (and you are not an LLM), you see the problem in a second, and you don’t need a finance degree. The bank has a review pipeline for exactly this.
Webwright: Why AI Web Agents Should Write Code, Not Click | Towards Data Science
Towards Data Science - Mediumby Chien Vu Minh·17 Aug 2026
1. Introduction: the web won’t hold still If you have built a web agent recently, you know the failure pattern.
Three Generations of Autoscaling — And Why Agentic Traffic Breaks All of Them | Towards Data Science
Towards Data Science - Mediumby Shoumik Chakravarty·17 Aug 2026
Intro In my organization I’ve worked as a backend engineer and architect. My main responsibility is ensuring the services we design meet their functional requirements, but also scale to millions of...
How to Perform Effective Project Management with AI | Towards Data Science
Towards Data Science - Mediumby Eivind Kjosbakken·17 Aug 2026
In this article, I’ll discuss how to perform effective project management in the age of AI, both from the perspective of orchestrating tasks and deciding what can be done, and then how to...
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