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 deep learning primarily inspired by?

• The structure of a computer

• The structure of a neural network

• The structure of the human brain

• The structure of a machine

What is the fundamental unit of the human brain that inspired perceptrons?

• Dendrite

• Axon

• Cell body

• Neuron

What is the role of an activation function in a perceptron?

• To add bias to the weighted sum

• To multiply inputs by weights

• To decide if a neuron should be activated

• To connect neurons together

What is the process called when a neural network adjusts its weights to learn?

• Backpropagation

• Forward propagation

• Neural adjustment

• Weight tuning

What is a neural network with more than one hidden layer called?

• Complex neural network

• Layered neural network

• Shallow neural network

• Deep neural network

Which of the following is an example of an advanced neural network technique?

• Support vector machine

• Linear regression

• Convolutional neural network

• Decision tree

Why has deep learning become a distinct field of study?

• Because it does not use neural networks

• Because it is simpler than machine learning

• Due to its increasing popularity and complexity

• Due to its limited applications