Exploring AI part six: Explaining deep learning

03 June 2019 / Will Watson

Exploring AI part one: What on earth is AI anyway?

Exploring AI part two: Unpacking NLP 

Exploring AI part three: Explainable AI - lifting the lid off the black box 

Exploring AI part four: What is machine learning? 

Exploring AI part five: What is unsupervised learning? 

Exploring AI part six: Explaining deep learning

What is Deep Learning?

As Kris covered in his blog ‘Exploring AI part one: What on earth is Artificial Intelligence anyway?’ deep learning is a type of machine learning that is based on using Deep Neural Networks. To understand Deep Neural Networks, it is useful to illustrate the structure of simpler neural networks by breaking it down into its component parts and then recognising how they expand to become deeper neural networks that can answer increasingly complex questions.

Securing confidence in deep learning outputs can be a big leap to many businesses given the traditional modelling methods that clarify the intuitive contribution of all model inputs to the final output. To alleviate such reservations, we will look at the intuition a neural network uses to arrive at its optimal solution and see that it is not too dissimilar to standard regression modelling.

What are Neural Networks?

Find out more about deep learning in our latest blog post

>>Download your copy now.