What are the key components of a neural network?

The main parts are: 1. Input layer (gets the data), 2. Hidden layers (process and pull out patterns from the data), 3. Output layer (produces the result), 4. Weights and biases (trainable parameters adjusted to improve model accuracy), 5. Activation functions (add non-linearity), and 6. Loss function (measures how wrong the model's predictions are).