Maths is the biggest hurdle most people face in machine learning and it is not because "you're just bad at math".
You were probably just never taught maths in a fun and intriguing way.
My goal this year is to understand the maths for ML and make it simple for all of you.
How do I plan to achieve this?
- Use less math jargon
- Provide practical uses for the math using code
- Oversimplify things (only to a certain level)
- Use of visualisations like this 👇
Here's an example of "oversimplifying".
Let's try to define a Tensor.
Definition 1: "In mathematics, a tensor is an algebraic object that describes a relationship between sets of algebraic objects related to a vector space....."