Introduction to Neural Networks

September 29, 2021 | 8:40 am
Timothy Flack & Annelies Gerber, Royal Mail

Please complete the form to watch the webinar recording


    You can watch the video below. Let us know if you learn something new or useful by tweeting us @DataIdols.

    An introduction to neural networks with a brief history is given. Traditional machine learning (ML) techniques are highlighted and compared with neural networks (NN).

    An overview of the constituent parts of a neural network is given( a node, layer, activation function, loss function, optimiser) is given with a summary to illustrate the neural network architecture. A Python example for movie review classification is then presented. Neural networks with memory (RNN, LSTM) are introduced briefly. Then, convolutional neural networks (CNN) are introduced with their building blocks (convolutional operation, padding, pooling, border effects) and an example is given using image classification (cats vs dogs).

    Mmm 🍪cookies!

    We use cookies to make your experience on this website better, and we have a variety to choose from. Use the toggles below to customise your selection or click 'Save my cookies' to get straight to the content.