Neural Network

Data Augmentations for n-Dimensional Image Input to CNNs

One of the greatest limiting factors for training effective deep learning frameworks is the availability, quality and organisation of the training data. To be good at classification tasks, we need to show our CNNs etc. as many examples as we possibly can. However, this is not always possible especially in situations where the training data is hard to collect e.g. medical image data. In this post, we will learn how to apply data augmentation strategies to n-Dimensional images get the most of our limited number of examples.

A Simple Neural Network - With Numpy in Python

Part 4 of our tutorial series on Simple Neural Networks. We’re ready to write our Python script! Having gone through the maths, vectorisation and activation functions, we’re now ready to put it all together and write it up. By the end of this tutorial, you will have a working NN in Python, using only numpy, which can be used to learn the output of logic gates (e.g. XOR)

A Simple Neural Network - Mathematics

This is the first part of a series of tutorials on Simple Neural Networks (NN). Tutorials on neural networks (NN) can be found all over the internet. Though many of them are the same, each is written (or recorded) slightly differently. This means that I always feel like I learn something new or get a better understanding of things with every tutorial I see. I’d like to make this tutorial as clear as I can, so sometimes the maths may be simplistic, but hopefully it’ll give you a good unserstanding of what’s going on. Please let me know if any of the notation is incorrect or there are any mistakes - either comment or use the contact page on the left.