Johan Blog

Streamlining LaTeX Workflow with VSCode: An Essential Guide

Publish on: 2023/04/05 Classify at: RESOURCE HUB/LaTeX

Ditch Overleaf for local speed. A complete guide to setting up a professional LaTeX environment with VS Code + TeX Live + SumatraPDF, including synctex support for forward/inverse search.

PMx-02: Building Blocks – Probability Distributions for Modelers

Publish on: 2023/02/14 Classify at: RESEARCH/Pharmacometrics

A practical review of the probability distributions central to pharmacometric modeling: from the Binomial to the Multivariate Normal. Understanding the building blocks before we build the model.

PMx-01: Foundations – The Leap from Sample to Population

Publish on: 2023/02/13 Classify at: RESEARCH/Pharmacometrics

Establishing the fundamental distinction between Population and Sample, between Probability and Statistical Inference. Why modeling is reverse engineering, and why code is not a model.

PMx-00: Preface – From 'How' to 'Why': Rethinking Your Modeling Mindset

Publish on: 2023/02/12 Classify at: RESEARCH/Pharmacometrics

An introduction to a blog series on pharmacometric statistics based on Adrian Dunne's workshop. Establishes the core philosophy: understand the 'Why' behind the algorithms, not just the 'How' of the software.

UML-10: Unsupervised Learning Series — Conclusion and Algorithm Guide

Publish on: 2022/10/10 Classify at: CODE/Unsupervised Machine Learning

The Explorer's Field Guide: A complete index of the Unsupervised Learning series, summarizing 9 algorithms with their core analogies and a master decision compass.

UML-09: Association Rule Mining

Publish on: 2022/10/09 Classify at: CODE/Unsupervised Machine Learning

Master Association Rules: The 'Symbiosis Scouter'. Learn how Apriori finds hidden partnerships (Support, Confidence, Lift) in your data ecosystem.

UML-08: Anomaly Detection

Publish on: 2022/10/08 Classify at: CODE/Unsupervised Machine Learning

Master Anomaly Detection: The 'Rare Species Hunter'. Learn how Isolation Forest (20 Questions) and LOF (Loneliness Index) find outliers in your data.

UML-07: t-SNE and UMAP for Visualization

Publish on: 2022/10/07 Classify at: CODE/Unsupervised Machine Learning

Master t-SNE and UMAP: The 'Origami Masters' of data. Learn how to unfold High-D 'crumpled paper' manifolds to reveal hidden structures that PCA misses.

UML-06: Principal Component Analysis (PCA)

Publish on: 2022/10/06 Classify at: CODE/Unsupervised Machine Learning

Master PCA: The 'Photographer' of data. Learn how to find the best camera angles (principal components) to capture the most detail (variance) in your data.

UML-05: Gaussian Mixture Models

Publish on: 2022/10/05 Classify at: CODE/Unsupervised Machine Learning

Master GMM: The 'Explorer in the Fog' of clustering. Learn how to map overlapping 'hills' of data, handle uncertainty with soft clustering, and master the EM algorithm.