2.4. Calculus — Dive into Deep Learning 1.0.0-beta0 documentation

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In deep learning, we also need to work with functions of many variables. Thus, evaluating the gradient requires computing a vector–matrix product. This is one of the key reasons why linear algebra is such an integral building block in building deep learning systems. a derivative is the rate of chang

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- In deep learning, we also need to work with functions of many variables.
- Thus, evaluating the gradient requires computing a vector–matrix product. This is one of the key reasons why linear algebra is such an integral building block in building deep learning systems.
- a derivative is the rate of change in a function with respect to changes in its arguments.
- The comment #@save is a special modifier that allows us to save any function, class, or other code block to the d2l package so that we can invoke it later without repeating the code, e.g., via d2l.use_svg_display().
- optimization problems

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