Machine learning is performed by any program that creates some model of something else from data. This is very broad and can include linear or polynomial regression, decision trees, and deep learning on artificial neural networks. Machine learning can also be when a program creates a model not just from static data, but from interaction, as is the case in many forms of reinforcement learning. Deep learning is when the model you are creating is a multi-layer artificial neural network. In the context of deep learning, these artificial neural networks are usually trained using gradient descent or a similar approach which takes into account the gradient of the loss such as the Adam optimizer. I can elaborate on any of those terms if they are confusing, but to summarize, all deep learning is machine learning, but not all machine learning is deep learning.
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