Neural networks

Artificial intelligence builds her strength on neural networks. With nodes and layers, she transforms inputs step by step into something meaningful. Here we see the core of how she learns.

• Neural network fundamentals – Core building blocks of neural networks.
• Gradient descent – Optimizing models by iteratively reducing error.
• Loss functions – Measuring model error during training.
• Overfitting – When models memorize training data instead of generalizing.