🐸 Welcome to Froge AI Tutorials: Neural Networks 🐸

Understanding Neural Networks

Neural networks are a subset of machine learning and are at the heart of deep learning algorithms. Their name and structure are inspired by the human brain, mimicking the way biological neurons signal to one another.

A neural network is made up of layers of nodes. Each node in a layer is connected to every node in the previous and following layers. The nodes apply various transformations to the input they receive and pass it to the next layer.

Key Components:

• Inputs: These are the initial data or features.
• Weights: These are the parameters learners adjust during training.
• Activation Function: Introduces non-linearity into the output.
• Output: This is the final prediction after transformation.