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I was always fascinated by the topic of Machine learning until I decided to teach myself how to do it. So I came through a course provided by Stanford published online. However, I was shocked at the amount of math it contained. So what is the mathematical background I should have to be able to understand the algorithms of machine learning? Are there any libraries that abstract all the maths and focuses on actually designing a software capable of learning?

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You should have a basic understanding of the followings:

  1. Python/R

  2. Linear algebra

  3. Probability theory

  4. Calculus

  5. Calculus of variations

  6. Graph theory

  7. Optimization methods (Lagrange multipliers)

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