Not Actually That Similar To Your Brain | AI 101

The video discusses neural networks, comparing them to the human brain. It highlights differences in structure, function, and learning processes. Neural networks are computational models with directionality, unlike the brain's complex, non-linear connections. The video explains how neural networks require preset architectures and are less energy-efficient than the brain. It concludes with a guide on building a neural network, emphasizing data loading, model training, and prediction.

What are perceptrons and how do they function within a neural network?

Explain the similarities and differences between neural networks and the human brain.

Describe the concept of back propagation in neural networks.

How does the learning process of computational neural networks differ from that of biological neural networks?

What are the implications of the fixed architecture in computational models?

Discuss the energy consumption differences between the human brain and neural networks.

What steps are involved in creating a functional neural network?