>>13272921>>13273717>>13273713I fell for this meme image because I wanted to get into ML/modern stats. I am a molecular biology grad and my background in math only goes up to Calc III (multivariable). Durrett's probability theory and examples absolutely requires at least some sort of background in real analysis and basic set theory, as well as an intro to measure theory. The first chapter skips most knowledge on measure theory and there is a quite lengthy appendix that goes over measure theory. If you are not a math major and you do not plan on proving theorems or you don't REALLY love math and are more interested in the applications, then this track seems excessive.
I would recommend an intro to probabilty theory by bertsekas, which is what I'm reading right now. It's at the perfect level for someone with little to no analysis background and it still gets into reasonable detail with regards to probability theory, minus most of the rigorous proofs, replacing them with more intuitive, barebones "proofs." It's an excellent textbook with some great examples, and you can probably move onto "real" probability theory that doesn't exclude measure theory afterwards. Durrett's probability theory actually alludes several times to the expectation that it was expected that a reader of the book has taken a course on introductory probability theory already.
In short, the dude who made that chart is a retard. I've made the mistakes and wasted months going through textbooks I'm not qualified for already. For you, OP. Check out bertsekas.
