Deep Learning

The video introduces deep learning as a subset of machine learning, explaining its inspiration from the human brain's structure. It covers the concept of neurons and perceptrons, activation functions, and the structure of artificial neural networks. The learning process through backpropagation is detailed, along with the complexity of deep neural networks. Advanced techniques like convolutional and recurrent neural networks are also discussed, highlighting the evolution of deep learning as a distinct field.

What is the relationship between machine learning and deep learning?

Explain the concept of a perceptron in the context of neural networks.

What role do activation functions play in a neural network?

How do weights affect the learning process in a neural network?

Describe the process of backpropagation in neural networks.

What distinguishes a deep neural network from a regular neural network?

What are some advanced techniques developed to improve neural network performance?