Gradient descent by matrix multiplication

Posted on Thu 23 February 2017 in blog • Tagged with python, data science, machine learning, math

Deep learning is getting so popular that even Mark Cuban is urging folks to learn it to avoid becoming a "dinosaur". Okay Mark, message heard, I'm addressing this guilt trip now. I originally tried starting in tensorflow (tensors are multidimensional arrays), but I quickly realized that I don't think in terms of tensors/matrices. For example, I drew a blank when thinking about how to take a partial derivative using matrix multiplication. So, as an exercise to understand concepts such as notation and matrix computations, my goal is to implement gradient descent on a multiple regression model.

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