The Naive Bayes Algorithm is a simple and elegant approach for tackling supervised learning problems in Machine Learning. This post will be a brief introduction…
Continue reading → Naive and Proud: Introducing the Naive Bayes Algorithm
If you’re like me, you’ve heard a lot about Gradient Descent. You’ve heard that it is a foundational algorithm for optimising functions which all self…
Continue reading → Gradient Descent: The Workhorse of Machine Learning
Job searching can be irritating at best and hopelessly frustrating at worst. This is particularly true in Data Science where the field is still relatively…
Recently I was thinking about the gradient descent algorithm and I was bothered was one question - Why do we go in the direction of…
Introduction Recently, Quanta magazine published an article about how a new basic identity about Linear Algebra has surfaced from Applied Physics. The identity is about…
Continue reading → Eigenvectors from Eigenvalues – Application
In this post I will build on the previous posts related to probability theory - I have defined the main results of probability from axioms…
Continue reading → Random Variables and Probability Functions
Prologue Earlier my career I worked for a loyalty card scheme for one of the largest supermarkets in the UK. During my time I was…
Continue reading → Market Basket Analysis – The Apriori Algorithm
Impostor syndrome is a real feeling and I get it at least twice a day with respect to what I do. Sure, I have a…
Continue reading → “It’s Not Special” – The Best Advice I Ever Had
After the last post discussing set theory here, the next logical step is to discuss the concept of probability theory. The theory of probability is…
Recently I have been undertaking a project to commit my accrued notes relating to statistics online. I want to do this for a few reasons:…