What are some popular deep learning architectures?
Some popular deep learning architectures include Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), and Transformers.
Can you explain how CNNs work?
Sure! CNNs are designed to process data with a grid-like topology, such as images. They use convolutional layers to automatically learn spatial hierarchies of features.
What are Transformers used for?
Transformers are primarily used in natural language processing tasks, such as translation and text generation, due to their ability to handle long-range dependencies.
How do RNNs differ from CNNs?
RNNs are designed for sequential data, making them suitable for tasks like time series analysis, while CNNs excel in spatial data like images.
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