Ground Zero

An Overview of Deep Learning — from History to Fundamentals

A playbook to learn the essentials behind deep learning focused on convolutional neural networks

Photo by Raimond Klavins on Unsplash

I recently taught a mini-course on Machine Learning 101 for those who want to become data scientists. One of its modules was about Deep Learning. I found that many newbies are confused with this topic, mainly because it is often taught with many complexities. In this article, I aim to describe it simply enough but not too simply. Hope it helps!

The article has four sections as follows:

• What is a Neural Network?
• What is Deep Learning?
• How to build a simple deep learning architecture?
• How to train a deep learning model?

What is a Neural Network?

A neural network is a computational model inspired by the biological neural network that processes information in the human brain. A neural network consists of a set of artificial neurons organized in layers (input, hidden, and output). These artificial neurons are connected by synapses that are just weighted values.

— What are the Building Blocks?