Artificial Neural network basics
Introduction to Artificial Neural Networks Neural Networks are a subset of machine learning models inspired by the structure and function of the human brain. They are designed to recognize patterns and learn from data, making them powerful tools for tasks such as image recognition, natural language processing, and predictive analytics. 1. Basic Structure Neurons : The fundamental building block of a neural network is the neuron (or node). Each neuron receives input, processes it, and sends output to other neurons. Layers : Neural networks are composed of layers of neurons: Input Layer : This is where the network receives the initial data. Hidden Layers : These layers process the inputs received from the input layer. A network can have multiple hidden layers. Output Layer : This layer produces the final output of the network. 2. Types of Neural Networks Feedforward Neural Networks : The simplest type, where connections move only in one direction—from input to output. Convolutiona...