Neural networks and deep learning
Neural networks, also known as artificial neural networks, are an ML paradigm inspired by animal neurons. A neural network consists of many nodes, playing the role of neurons, connected via edges, playing the role of synaptic connections. Typically, the neurons are arranged in layers, with each layer fully connected to the next. The first and last layers are input and output layers, respectively. Inputs may be continuous (but often normalized to [-1, 1]) or binary, while outputs are typically binary or probabilities. The network is trained by repeatedly examining the training set. Each repetition on the full training set is called an "epoch." During each epoch, the weights on each edge are slightly adjusted in ...
Get AI Blueprints now with the O’Reilly learning platform.
O’Reilly members experience books, live events, courses curated by job role, and more from O’Reilly and nearly 200 top publishers.
