Forever Student, Always Learning

Explore the fundamentals of Bayesian statistics and how it differs from frequentist approaches. Learn to think probabilistically about uncertainty and evidence.

Understanding how neural networks learn through backpropagation, with complete mathematical derivations and practical implementation from scratch. We have derived all the code from scratch in python and all the math was derived.

A deep dive into the mathematical foundations of linear regression, including derivations and practical implementations.

Practical tips to improve your data science workflow, from project organization to reproducible analysis.

Welcome to my new blog! Learn about the features, LaTeX support, and what you can expect from future content.