Bifalgorithm post

How much math do you actually need for machine learning and to be successful at it? And it's not as bad as you think. It's roughly 35% linear algebra, 35% probability in stats and 30% calculus. For linear algebra, you're going to want to use this course right here, which is completely free from MIT. It gets you comfortable vectors and matrix multiplication. For calculus use this right here. It takes you through single and multivariable calculus and differential equations, which is basically solving for a value that depends on the rate of change of something else. For probability and stats, a really good resource for you to take is the Intro to Probability course taught by Harvard professors. This is completely free online as a PDF. And for machine learning specifically, there's a ton of algorithms you can learn about, but you don't need to know the math in depth to use them. But you can use this book right right here if you still want to learn it teaches you the math behind it and how to use each of these algorithms I've used all these resources and it can honestly take you a ton of time just figuring out exactly what you need since there is so much content So I built an app where you can learn everything you need in one singular place for machine learning and I made it as fun as possible and I launched recently so comment math if you want the link and follow for more

How much math do you actually need for machine learning and to be successful at it? And it's not as bad as you think. It's roughly 35% linear algebra, 35% prob…