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Hello and welcome to my neural network, I will be discussing how neural networks learn with diffrent sets of data and images. The first thing you need to know is activaiton functions. There are many activation functions as shown on the right, 'relu', 'sigmoid', and 'leakyrelu' are reccomended when creating a neural network for scientific purposes. Many Large Neural Network models use GELU as the activation function, this is because they need to process large amounts of data on both the input and output. Neural Networks have layers that process the inputed data, there is the inner layer, middle layer, and outer layer which displays the predicted values from the inputed data. Each layer consists of many nodes that process data by adjusting values between 0-1. Neural Networks learn when you input data and train it to correctly adjust those nodes so that when it outputs data it will predict data with certain accuracy.
