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Setting a derivative to zero helps find the minimum or maximum points of a function, which represents the best possible model configuration. 3. Partial Derivatives
When you open those PDFs, you will be tempted to read everything. As an ML engineer, you only need four specific pillars of calculus. Here is your cheat sheet:
The "Chain Rule" in action, allowing neural networks to update weights across many layers.
Training an ML model means minimizing a "loss function" (a measure of error). Calculus allows us to find the lowest point of this function.
If ( y = f(u) ) and ( u = g(x) ), then: