Neural networks and deep learning
Inspired by human brain biology, artificial neural networks (ANNs) are good at processing unstructured data such as images, audio, and text and are widely used in image recognition, speech recognition, and natural language processing (NLP). These are their fundamental blocks:
- Neurons and layers: ANNs apply parallel processing by using nodes called neurons. Each node has a weight and a bias, both of which are used to produce their output based on outputs. Neurons are organized in layers, and typically, there is an initial input and final output layer, and layers in between called hidden layers where the actual computation takes place. Inputs to each layer are derived from the outputs of the previous layer.
- Training and weights update: Training an ANN involves adjusting the weights and biases of neurons based on error. This consists of a process called backpropagation and an optimization method, such as batch gradient descent and/or stochastic...
