How Much Math Do You Need for Data Science?

Subscribe to RichardOnData here: https://www.youtube.com/channel/UCKPyg5gsnt6h0aA8EBw3i6A?sub_confirmation=1 See my video on how much statistics you really need for data science here: https://www.youtube.com/watch?v=_tEek2jPn-4 In this video, I talk about how much math you really need for data science, looking at two broad categories: calculus, and linear algebra. My contention is, you don't need as much as you probably think you do. Case in point, see the book "An Introduction to Statistical Learning with Applications in R" -- there is very little calculus in this book. See this article for a discussion on distinction between practical and theoretical data science: https://www.sharpsightlabs.com/blog/math-for-data-science/ I highly recommend this book for linear algebra purposes: https://amzn.to/3ihktwA See also: https://medium.com/s/story/essential-math-for-data-science-why-and-how-e88271367fbd https://www.dataquest.io/blog/math-in-data-science/ https://towardsdatascience.com/from-eigendecomposition-to-determinant-fundamental-mathematics-for-machine-learning-with-1b6b449a82c6 My personal favorite resource for math: https://tutorial.math.lamar.edu/