A gentle introduction to neural networks, and making your own with Python.
This session is especially designed to be accessible to everyone, including anyone with no expertise in mathematics, computer science or Python.
From this session you will have an intuitive understanding of what neural networks are and how they work. If you are more technically capable, you will see how you could make your own with Python and numpy.
Part 1 - Ideas:
- the search for AI, hard problems for computers easy for humans
- learning from examples (simple classifier)
- biologically inspired neurons and networks
- training a neural network
- the back propagation breakthrough
- matrix ways of working (good for computers)
Part 2 - Python:
- Python is easy, and everywhere
- Python notebooks
- the MNIST data set
- a very simple neural network class
- focus on concise and efficient matrix calculations with numpy
- 97.5% accuracy recognising handwritten numbers - with just a few lines of code!
Part 3 - Live Demo! … and Q&A