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41554 blogs · [ { "id": "01a08721-8194-7043-900f-46696a14a4fe", "title": "Code Quality Shouldn't Have a Bus Factor of One", "url": "https://www.aidancooper.co.uk/code-quality-shouldnt-have-a-bus-factor-of-one/", "published_at": "2026-04-19T23:31:03+00:00" }, { "id": "01a08721-8194-7043-900f-46696ae3381a", "title": "PGN2FEN: A Benchmark for Evaluating LLM Chess Reasoning", "url": "https://www.aidancooper.co.uk/pgn2fen-benchmark/", "published_at": "2025-05-03T16:59:44+00:00" }, { "id": "01a08721-8194-7043-900f-46696bcf7718", "title": "The Convergence of Proprietary and Open Source LLMs", "url": "https://www.aidancooper.co.uk/the-convergence-of-proprietary-and-open-source-llms/", "published_at": "2024-08-12T08:37:12+00:00" }, { "id": "01a08721-8194-7043-900f-46696c566e3a", "title": "How to Beat Proprietary LLMs With Smaller Open Source Models", "url": "https://www.aidancooper.co.uk/how-to-beat-proprietary-llms/", "published_at": "2024-04-26T14:22:37+00:00" }, { "id": "01a08721-8194-7043-900f-46696cffc897", "title": "A Guide to Structured Generation Using Constrained Decoding", "url": "https://www.aidancooper.co.uk/constrained-decoding/", "published_at": "2024-04-08T11:00:00+00:00" }, { "id": "01a08721-8194-7043-900f-46696de0d997", "title": "Modern Data Engineering and the Lost Art of Data Modelling", "url": "https://www.aidancooper.co.uk/the-lost-art-of-data-modelling/", "published_at": "2023-07-22T09:40:53+00:00" }, { "id": "01a08721-8194-7043-900f-46696ec9b667", "title": "Machine Learning in the Life Sciences Has a Data Problem", "url": "https://www.aidancooper.co.uk/ml-in-the-life-sciences/", "published_at": "2023-06-23T08:10:38+00:00" }, { "id": "01a08721-8194-7043-900f-46696ee26ba8", "title": "Approximating Shapley Values for Machine Learning", "url": "https://www.aidancooper.co.uk/approximating-shapley-values/", "published_at": "2023-06-07T08:16:26+00:00" }, { "id": "01a08721-8194-7043-900f-46696f01d19d", "title": "Gnillehcs' Model of Integration", "url": "https://www.aidancooper.co.uk/gnillehcs/", "published_at": "2023-04-07T11:12:22+00:00" }, { "id": "01a08721-8194-7043-900f-46696fdf1d87", "title": "How Shapley Values Work", "url": "https://www.aidancooper.co.uk/how-shapley-values-work/", "published_at": "2022-12-31T10:17:56+00:00" }, { "id": "01a08721-8194-7043-900f-4669704496bf", "title": "Industry Perspective: Tree-Based Models vs Deep Learning for Tabular Data", "url": "https://www.aidancooper.co.uk/tree-based-models-vs-deep-learning/", "published_at": "2022-08-13T10:58:08+00:00" }, { "id": "01a08721-8194-7043-900f-4669708f8380", "title": "4 Pandas Anti-Patterns to Avoid and How to Fix Them", "url": "https://www.aidancooper.co.uk/pandas-anti-patterns/", "published_at": "2022-07-11T07:53:42+00:00" }, { "id": "01a08721-8194-7043-900f-466970d2732b", "title": "Supervised Clustering: How to Use SHAP Values for Better Cluster Analysis", "url": "https://www.aidancooper.co.uk/supervised-clustering-shap-values/", "published_at": "2022-05-16T07:49:38+00:00" }, { "id": "01a08721-8194-7043-900f-466970fefe59", "title": "Utility vs Understanding: the State of Machine Learning Entering 2022", "url": "https://www.aidancooper.co.uk/utility-vs-understanding/", "published_at": "2022-01-02T11:07:54+00:00" }, { "id": "01a08721-8194-7043-900f-4669710eef24", "title": "Explaining Machine Learning Models: A Non-Technical Guide to Interpreting SHAP Analyses", "url": "https://www.aidancooper.co.uk/a-non-technical-guide-to-interpreting-shap-analyses/", "published_at": "2021-11-01T13:00:42+00:00" } ] posts Claim your blog
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aidancooper.co.uk

aidancooper.co.uk

2026

Code Quality Shouldn't Have a Bus Factor of Oneoriginal ↗
19 Apr 2026

2025

PGN2FEN: A Benchmark for Evaluating LLM Chess Reasoningoriginal ↗
3 May 2025

2024

The Convergence of Proprietary and Open Source LLMsoriginal ↗
12 Aug 2024
How to Beat Proprietary LLMs With Smaller Open Source Modelsoriginal ↗
26 Apr 2024
A Guide to Structured Generation Using Constrained Decodingoriginal ↗
8 Apr 2024

2023

Modern Data Engineering and the Lost Art of Data Modellingoriginal ↗
22 Jul 2023
Machine Learning in the Life Sciences Has a Data Problemoriginal ↗
23 Jun 2023
Approximating Shapley Values for Machine Learningoriginal ↗
7 Jun 2023
Gnillehcs' Model of Integrationoriginal ↗
7 Apr 2023

2022

How Shapley Values Workoriginal ↗
31 Dec 2022
Industry Perspective: Tree-Based Models vs Deep Learning for Tabular Dataoriginal ↗
13 Aug 2022
4 Pandas Anti-Patterns to Avoid and How to Fix Themoriginal ↗
11 Jul 2022
Supervised Clustering: How to Use SHAP Values for Better Cluster Analysisoriginal ↗
16 May 2022
Utility vs Understanding: the State of Machine Learning Entering 2022original ↗
2 Jan 2022

2021

Explaining Machine Learning Models: A Non-Technical Guide to Interpreting SHAP Analysesoriginal ↗
1 Nov 2021