*Learning the theoretical background for data science or machine learning can be a daunting experience, as it involves multiple fields of mathematics, and a long list of online resources.*

Here’s an article by the awesome I will divide the resources to 3 sections (Linear Algebra, Calculus, Statistics and probability), the list of resources will be in no particular order, resources are diversified between video tutorials, books, blogs, and online courses.

Used in machine learning (& deep learning) to understand how algorithms work under the hood.

That looks complicated, but we can break it down into pretty manageable pieces: Math we need: If you want to scrape the surface of Naïve Bayes’ classifier algorithms and all the uses for Bayes’ theorem, a course in probability would be sufficient.

To get an introduction to probability, you can check out our course on probability and statistics.

Well, we see right over here, four out of the 35 liked rap music.

So based on this survey, this would really just be an estimate of the true probability, but based on this survey out of 35, four liked rap music.Math is like an octopus: it has tentacles that can reach out and touch just about every subject.And while some subjects only get a light brush, others get wrapped up like a clam in the tentacles’ vice-like grip. If you want to do data science, you’re going to have to deal with math. In this post, we’re going to explore what it means to do data science and talk about just how much math you need to know to get started.These suggestions are derived from my own experience in the data science field, and following up with the latest resources suggested by the community.However, if you are a beginner in machine learning and looking to get a job in industry, I don’t recommend studying all the math before starting to do actual practical work, this bottom up approach is counter-productive and you’ll get discouraged, as you started with the theory ().Statistics is the only mathematical discipline we mentioned in that definition, but data science also regularly involves other fields within math.Learning statistics is a great start, but data science also uses algorithms to make predictions.According to the survey, what is the probability that a male likes rap music?So let's look at the total number of males surveyed.So there's 35 males that were asked what is there musical preference.And we wanna know what is the probability that a male likes rap music according to the survey. So out of the 35 males, how many of them liked rap music?

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