This channel is all about machine learning (ML). It contains all the useful resources which help ML lovers and computer science students gain a better understanding of the concepts of this successful branch of Artificial Intelligence.
Thanks very much, I was looking for such videos to answer my assignment questions and you answered all of them at once within 3 minutes. I salute you,please keep on do more videos to assist the students to pass their exams and assignments.
Hey! Thanks for the fantastic content :) I'm trying to understand the additivity axiom a bit better. Is this axiom the main reason why Shapley values for machine learning forecast can just be added up for one feature over many different predictions? Let's say we can have predictions for two different days in a time series and each time we calculate the shapley value for the price value. Does the additivity axiom then imply that I can add up the Shapley values for price for these two predictions (assuming they are independent) to make a statement about the importance of price over multiple predictions?
Why are the given weights for the distributions, are not really showcasing the distributions on the graph. I mean i would choose π1 = 45, π2 = 35, π3 = 20
Two things: 1. What the H matrix is has not been described. 2. One non s1x1 matrix cannot be smaller or greater then another. This is sloppy. Besides that, it is a great work.
Hi, about the sample has X1 to Xn, do X1 and Xn have to be different? Because you have a previous sample of 100 height from 100 different people. Or it can be like we treated in bootstrap that X1* to Xn* can be drawn randomly from X1 to Xn so basically can draw same height of a single person?
I believe there might be an issue with the perplexity formula. How can we refer to 'w' as the test set containing 'm' sentences, denoting 'm' as the number of sentences, and then immediately after state that 'm' represents the number of all words in the entire test set? This description lacks clarity and coherence. Could you please clarify this part to make it more understandable?
I have run into token exhaustion while working with GPT4 specifically when it is giving programming language output. Im assuming resolving this will be a component of GPT5...
