Sebastian Raschka

Implementing a Principal Component Analysis In Python (2014)

Implementing Principal Component Analysis from scratch in Python: scatter matrices, eigenvectors, variance explained, and comparison with scikit-learn PCA.

A Short Chronology of Deep Learning for Tabular Data

Occasionally, I share research papers proposing new deep learning approaches for tabular data on social media, which is typically an excellent discussion…

Optimizing LLMs from a Dataset Perspective

Practical guide to improving LLM finetuning with better instruction datasets, covering data curation, prompt-output pairs, synthetic data, and experiment ideas.

Naive Bayes and Text Classification I – Introduction and Theory

Naive Bayes classifiers, a family of classifiers that are based on the popular Bayes’ probability theorem, are known for creating simple yet well performing…

An introduction to parallel programming using Python's multiprocessing module