Introduction to neural networks

One of the fundamental premises of AI is to build systems that can perform tasks that would normally require human intelligence. The human brain is amazing at learning new concepts. Why not use the model of the human brain to build a system? A neural network is a model designed to loosely simulate the learning process of the human brain.

Neural networks are designed such that they can identify the underlying patterns in data and learn from them. They can be used for various tasks such as classification, regression, and segmentation. One drawback of neural networks is that we need to convert any given data into a numerical format before feeding it into the neural network. For example, we deal with many different types of data including visual, textual, and time series. We need to figure out how to represent problems in a way that can be understood by neural networks. To understand this process, let's first consider how to build a neural network...