I've begun to panic about my performance in this course. In particular, the midterm exam and final exam where preparation is critical.
I'm asking a question specific to Part 5 Video 9 for "Machine Learning" and maximizing the likelihood. The title is "Maximum Likelihood_1".
Could someone who is more versed in the algorithms shown in this video and the mathematics to support it provide a step by step explanation of what Prof. Thurn is doing/accomplishing? I'm asking for clarification, not to break the honor code.
The professor does note that this is not important to the course, but I would feel at a greater disadvantage than I do already if I don't understand it more deeply.
I think it was mostly just the higher math (Statistics, Calculus, Trig, etc.) that goes into converting a formula from one form to another. For example converting velocity = distance / time into distance = velocity * time. He's done this several times where I just space out because I can't follow what he is doing. At the end he shows us an equation that we actually use to solve the problem. All the higher math is simply proving why that formula works.
I agree that understanding that that math could help to understand the concepts the formula represents. However, I think knowing and being able to use the formula is much more important for your grade.
answered 03 Nov '11, 20:02