What are the key concepts in deep learning?

What are the key concepts in deep learning?

Deep learning is a subset of machine learning that uses neural networks with many layers. Key concepts include neural networks, activation functions, backpropagation, and overfitting.

Can you explain what a neural network is?

A neural network is a computational model inspired by the human brain, consisting of interconnected nodes (neurons) that process data.

What is backpropagation?

Backpropagation is an algorithm used to train neural networks by minimizing the error between predicted and actual outputs through gradient descent.

How do activation functions work?

Activation functions introduce non-linearity into the model, allowing it to learn complex patterns. Common examples include ReLU, sigmoid, and tanh.

What is overfitting and how can it be prevented?

Overfitting occurs when a model learns the training data too well, including noise. It can be prevented using techniques like regularization, dropout, and early stopping.