Normally, I say the best way to get started with machine learning is to do machine learning. So, strictly speaking, there’s no “required math” to get started and follow along with online tutorials. However, if you want to take your AI game to the next level, then it’s time to get deep into the math.

Data Science Central outlines specifics around the subjects to tackle and where to find them online.

- Linear Algebra — Professor Strang’s textbook and MIT Open Courseware course are recommended for good reason. Khan Academy also has some great resources, and there is a helpful set of review notes from Stanford.
- Multivariate Calculus — Again, MIT Open Courseware has good courses, and so does Khan Academy.
- Probability — Stanford’s CS 229, a course I’ve mentioned later, has an awesome probability review worth checking out.

## Comments

## AI, Ethics, and Unintended Consequences

## 5 Steps to Ace Data Science Interviews

## How to Determine the Line Between Data and Big Data by Going to Costco

## How to Determine the Line Between Data and Big Data by Going to Costco

## How to Determine the Line Between Data and Big Data by Going to Costco