What is the difference between deep learning and neural networks?

What is the difference between deep learning and neural networks?

Deep learning is a subset of machine learning that uses neural networks with many layers. Neural networks are the architecture used in deep learning.

Can you explain how neural networks work?

Sure! Neural networks consist of layers of interconnected nodes (neurons) that process input data and learn patterns through training.

What are some applications of deep learning?

Deep learning is used in various applications like image recognition, natural language processing, and autonomous vehicles.

Are there any limitations to deep learning?

Yes, deep learning requires large amounts of data and computational power, and it can be prone to overfitting if not managed properly.