
Encoding in Machine Learning: Designing Categorical Geometry
A geometric and statistical exploration of encoder families — from categorical mappings to latent spaces, positional signals, and semantic retrieval encoders

A geometric and statistical exploration of encoder families — from categorical mappings to latent spaces, positional signals, and semantic retrieval encoders

A theoretical and practical exploration of Directed Acyclic Graphs for data pipelines

A comprehensive guide to energy forms, SI measurement standards, and practical feature engineering strategies for data scientists building physics-aware ML models with real-world battery discharge example

Core signal processing operations that underpin all speech recognition and synthesis systems.

Introduction Time series analysis evolved from early astronomical observations and economic studies in the 1920s. Box and Jenkins revolutionized the field in the 1970s with ARIMA models, while the...

Project Management for ML Developpement

A simple Overview

Describing text operations and transformations in neural networks

Archived insight from languages before talking about natural languages

Explaining virtualisation & containerisation using a unix-based os