Deep neural networks (DNNs) are powerful models that use linear algebra and activation functions to process input data and learn from it through the…
Browsing: Activation Functions
Artificial Intelligence (AI) is powered by neural networks, computational models inspired by the human brain. Neural networks consist of three main types of layers:…
This thesis investigates two potential directions to advance deep learning. The first paper studies generalisation of neural networks with rectified linear activations units (“ReLUs”)…
This blog post introduces the fundamental concepts of deep learning and explores how neural networks work. Topics discussed include the perceptron, linear classifiers, activation…