# Tag Info

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This may help, the labs and associated materials for a course CSC 294: Computational Machine Learning: github link. See course-materials/Labs/, Jupyter Notebooks: k-means PCA SVD k-NN Gradient descent SVM Decision trees Deep learning

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You have asked two very different questions. I'll leave the differential equations for someone else. There is one particular application of integration which is my favorite last problem to do in Calc I. (We got behind this semester, and I was very sad not to have time for this. It feels like a perfect grand finale to me.) You probably learned the formula for ...

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It is probably not the place of mathematics educators to decide what mathematics courses engineering majors should take. But a good reference point is ABET accreditation. Over 600 universities in the US have ABET accredited engineering programs. We should defer to the professionals who set these standard and assess outcomes. Here is a description of their ...

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Well it doesn't really feel right to get degrees in engineering and gain years of engineering experience without even knowing what a limit actually is. And even though many engineers will do just fine without having been exposed to the rigorous definition of a limit, some engineers will need to be familiar with rigorous definitions/proofs if they ever pursue ...

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Dustin Mixon at The Ohio State University has written rigorous notes on the Mathematics of Data Science that cover both "fundamentals" (matrix analysis, convex optimization, probability) and "applications" (dimensionality reduction, clustering, compressed sensing). These notes are pitched at a reasonably high graduate level, but they ...

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A good approach for engineers might be to connect the "slope of a graph" to sensitivity: the factor by which a small change in input gets multiplied to produce a change in the output. You can connect this to both understanding how changes propagate through a system and error analysis. You can either do this purely symbolically to derive the ...

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The concepts behind limits are actually very important to engineering (in the form of error/precision analysis), but are rarely phrased that way. Given a function $f$, we can imagine an engineering situation where there is some desired range of outputs from the function, but the engineer has control over the value of the inputs of the function. If $f(c) = L$,...

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I am sure you will enjoy this Mathematics for Machine Learning specialization by UCL

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No, it's definitely not "necessary". I'm not an engineering major, but roomed with one, did a general engineering minor, and worked in/around mechanical, nuclear, mining and chemical engineering (had electrical on staff too). Passed my EIT and was at one time, about to take the PE (mechanical) exam. Most engineers in the workplace don't even use ...

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