What is the difference between neural networks and deep learning?

What is the difference between neural networks and deep learning?

Neural networks are a subset of machine learning algorithms inspired by the human brain, while deep learning is a type of neural network with many layers that can learn from vast amounts of data.

Can you explain how deep learning works in more detail?

Sure! Deep learning uses multiple layers of neurons to process data. Each layer extracts features, allowing the model to learn complex patterns.

What are some real-world applications of deep learning?

Deep learning is used in various applications, including image and speech 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 less interpretable compared to simpler models.