What are the key differences between machine learning and deep learning?

What are the key differences between machine learning and deep learning?

Machine learning is a subset of AI that uses algorithms to analyze data, while deep learning is a subset of machine learning that uses neural networks.

Can you explain how neural networks work in deep learning?

Neural networks consist of layers of interconnected nodes that process data, learning patterns through training on large datasets.

Are there specific applications where deep learning outperforms machine learning?

Yes, deep learning excels in tasks like image and speech recognition, where it can learn complex patterns from vast amounts of data.

What are some common algorithms used in machine learning?

Common algorithms include decision trees, support vector machines, and k-nearest neighbors, each suited for different types of data.

Is deep learning always better than machine learning?

Not necessarily. Deep learning requires more data and computational power, so for simpler tasks, traditional machine learning may be more effective.