Math in AI

I have recently started looking into AI and have been playing with some AI models. But I want to understand how it works and therefore have started looking into the Math behind AI. I will share some of what I have learnt with a view to refining my findings as I learn more. Please feel free to comment with your understanding of Math in AI as that will enhance my learning.

Linear Algebra- It is what enables machines to handle vast amounts of data and find patterns. For example, matrices and vectors represent data, and AI algorithms manipulate them to recognize images, analyze speech, and predict future trends.

Calculus- It helps with finding optimum solutions through derivatives- i.e. fine-tuning models so they can make accurate predictions.

Probability- It allows AI to deal with uncertainty as decisions are based on probabilities, like predicting the next word in a sentence or determining the likelihood of an event happening.

Statistics- It allows for analyzing trends, testing hypotheses, and ensuring models are not just memorizing data but generalizing to new and unseen information.

What do you think? Next time, we will take a look more closely into each one od these areas and specifically understand the Math aspects. Let me know your thoughts and insights on this topic.