Deep learning models can be trained using various algorithms, including:
- Backpropagation: Backpropagation is an algorithm used to train neural networks by minimizing the error between the predicted output and the actual output.
- Stochastic gradient descent: Stochastic gradient descent is an algorithm used to optimize the parameters of a neural network by minimizing the loss function.
- Adam: Adam is an algorithm used to optimize the parameters of a neural network by minimizing the loss function.
In summary, deep learning is a subfield of machine learning that involves the use of artificial neural networks with multiple layers to analyze and interpret data. Neural networks are a key component of deep learning, and they are used to build deep learning models.