Handbook

Neural networks and deep learning play a critical role in pushing the boundaries of what AI can achieve, making them indispensable for various industries and applications. Their ability to learn and adapt from data has revolutionised many fields and opened up new opportunities for solving complex problems. This course provides an introduction to and deep exploration of neural networks and deep learning principles and practice.

Topics chosen from: perceptrons, feedforward neural networks, backpropagation, Hopfield and Kohonen networks, restricted Boltzmann machine and autoencoders, deep convolutional networks for image processing; geometric and complexity analysis of trained neural networks; recurrent networks, language processing, semantic analysis, long short term memory; designing successful applications of neural networks; recent developments in neural networks and deep learning.