Neural networks have played a critical role in recent advances in automation and artificial intelligence over the last decade - with applications in sectors as broad as medicine, driver-less cars and industrial process optimisation.
PyTorch and TensorFlow are the two leading machine learning frameworks. PyTorch is more pythonic in design, and so much easier to use and debug.
In this beginner-friendly tutorial we will:
* learn the basics of how a neural network works (without too much maths)
* learn the basics of PyTorch
* see the basic structure of PyTorch machine learning code
* build step-by-step a neural network with PyTorch that learns to classify images of hand-written digits, a standard machine learning challenge
* build the confidence to continue to learn about machine learning, and experiment with PyTorch
This is a session designed for beginners to both machine learning and PyTorch. You don't need to be an expert with coding and Python but a little experience with be helpful.
This is a hands-on practical tutorial. Please bring a fully charged laptop (access to power sockets not guaranteed), with working wifi and a modern browser like Chrome, Firefox or Safari.
There is no need to install Python, we will use the online Google Colab service. You'll need a Google Account for this, and if you log into Gmail or YouTube you already have one.