Convolution
Convolution is a mathematical operation that combines two functions to produce a feature map that highlights the most important features of the input data. It is widely used in Signal Processing, Image Processing, and Machine Learning to extract relevant information from data. In Neural Networks, convolution is used to scan the input data, such as images, to detect edges, lines, and other features. The Transformer architecture, introduced by Ashish Vaswani, also uses convolution to process input sequences. Convolution can be applied to various types of data, including Audio Signals, Images, and Time Series data, to analyze and understand the underlying patterns.