K-Fold Cross-Validation in Scikit-Learn: Tutorial

Exploring the Use of Randomly Generated Data for Model Pre-Training

The article explores the use of randomly generated data for pre-training models, supported by theoretical justifications and empirical evide

Statistical Challenges in Machine Learning Model Calibration and Isotonicity Constraints

The article discusses the challenges of post-hoc calibration in machine learning models, specifically addressing the 'deadweight costs of st

Critique of Train-Test Split Methodology for Advanced Machine Learning Tasks

The article critiques traditional train-test split methodology in machine learning, using a satirical case study about building a 'butt clas

Python AI and Machine Learning Projects for Beginners: A Step-by-Step Guide to Building Smart Apps and Automation Tools with Scikit-Learn, OpenAI, and TensorFlow

Pen-and-Paper Machine Learning Exercises: A GitHub Collection Covering Graphical Models, Inference, and Optimisation

A collection of pen-and-paper exercises in machine learning covering topics such as linear algebra, optimisation, graphical models (directed

Reflecting on Optimisation: A Personal Take on Theory vs. Modern Practice

Magnus Ross reflects on his lack of deep study in optimisation, admitting he knows the basics (Adam, AdaGrad, L-BFGS) but zones out when dis