I am required to complete a project on ML applications. I guess there is a lot of statistics in ML, not helpful for a non-maths background.
I am getting too bogged down by notations. There are too many notations.
I am trying to read about what Bernoulli trials are and I can't relate to it.
What is a Bayesian setting and why is Bayesian thing everywhere? What makes it such an omnipotent distribution?
Are there any theorems/theories that I must know ? Any book/notes/resources where I could learn about these stuff in a relatable way (I have very little maths background, but I can learn)?