Over the years, I’ve worked with talented Data Scientist’s who’s backgrounds weren’t in typical quantitative disciplines, such as mathematics or statistics. I’ve had the privilege of assisting some of them to better understand the underlying mathematics behind many commonly used Machine Learning and Deep Learning algorithms. This, along with the current growth in the popularity of…

# Category: Deep Learning

## Deep Learning? Take a Deep Breath!

Are you planning to jump on the shiny Deep Learning bandwagon? Have you taken a sip of the tasty Deep Learning Kool-Aid? There have been some incredible discoveries in the Data Science world over the past 70 years or so: 1950’s: The birth of Artificial Neural Networks, based on the mathematical model of a neuron…

## Deep Learning – Deeply Limited?

From a mathematical perspective, Deep Learning can effectively be defined as: The application of a set of complex geometric transformations to map the input space to the output space. In more detail, we are simply doing the following when developing a Deep Learning model: Vectorisation: convert input and output data into vectors ie positions of…

## How to Implement an Artificial Neural Network: An Intuitive Sojourn

The premise of this article is to discuss the intuition behind training an ANN. There will be no maths and no code, just discussion of some of the fundamental ideas. I will assume the reader has a basic understanding of a neural network. I aim to give the reader an understanding of the key concepts of ANNs,…