Artificial Neural Networks

Artificial Neural Networks (ANNs) are the foundation of deep learning. They consist of interconnected neurons (nodes) that process data in layers. An ANN typically includes an input layer, one or more hidden layers, and an output layer.

Key Features:

• Feedforward Networks: Data flows in one direction from input to output.
• Activation Functions: Apply non-linear transformations to the input (e.g., ReLU, Sigmoid).
• Backpropagation: A method to train the network by adjusting weights based on error rates.

Applications:

• Classification
• Regression
• Pattern recognition

Datasets:

Kaggle

Additional Reading:

• Yann LeCun et al.,1998, Efficient BackProp
• Michael Nielsen, 2015, Neural Networks and Deep Learning