Francis Galton's quote at the end and students clapping. Wow a wonderful lecture again! I am speeding through this like watching Netflix. Chris Piech is an awesome professor!
I watched every second from Lecture 1 to Lecture 17 in the past eight days. I cannot think of a better preperation for my Statistics final exam next month at my university in Germany. Many thanks to Chris and the TAs. What a wonderful course! Possibly the best around the globe.
@@omaraymanbakr3664 Hey, it went pretty well (thank you for asking), it was quite easy to pass after doing two courses (one online and one in real-life) simultaneously. The most difficult exam problem was on Maximum Likelihood Estimation. In retrospect, I would do as many exercises with pen and paper as possible on top of attending class and watching online content. Doing exercises with pen and paper is the surest and quickest way to an A.
@@omaraymanbakr3664 Statistics was a prerequisite to take the mandatory course in Machine Learning at my local university. I study Artificial Intelligence and almost all of my courses are mandatory courses. This term, I also have courses in Computer Vision and Optimization (think of Gradient Descent) among others. Do you study Computer Science or something related to Mathematics/Statistics?
@@rolandlochli4492 I have written this reply so many times, but it keeps being deleted, and I don't know why. Anyway, I am also studying machine learning (my end goal is computer vision). I am taking a machine learning course right now, and I realized that ML is just statistics with optimization and some advanced linear algebra! So, I was looking for a statistics course to take after this one, but I only found this one from Mit [18.650 | Fall 2016 | Undergraduate]. What do you think? Is it a good choice to take after this one? I am self-studying the field, so ...
Every time that I think it’s couldn’t be better I just encounter with another amazing lecture by Chris 👌👍😎 Hope to see more from him 🙏 (especially programming methodology !!)
I think the convolution part uses wrong notation f(X+Y=a) = integral (f(X=a-y)f(Y=y)dy), because obviously here there are 3 functions f, one for random variable A=X+Y, one for X and the other Y. All of them are represented by f
Francis Galton's quote at the end and students clapping. Wow a wonderful lecture again! I am speeding through this like watching Netflix. Chris Piech is an awesome professor!
I watched every second from Lecture 1 to Lecture 17 in the past eight days. I cannot think of a better preperation for my Statistics final exam next month at my university in Germany. Many thanks to Chris and the TAs. What a wonderful course! Possibly the best around the globe.
I am curious how did your exam go ?
@@omaraymanbakr3664 Hey, it went pretty well (thank you for asking), it was quite easy to pass after doing two courses (one online and one in real-life) simultaneously. The most difficult exam problem was on Maximum Likelihood Estimation.
In retrospect, I would do as many exercises with pen and paper as possible on top of attending class and watching online content. Doing exercises with pen and paper is the surest and quickest way to an A.
@@rolandlochli4492 well done .
Out of curiosity again 😅 which course did you choose after this one
@@omaraymanbakr3664 Statistics was a prerequisite to take the mandatory course in Machine Learning at my local university. I study Artificial Intelligence and almost all of my courses are mandatory courses. This term, I also have courses in Computer Vision and Optimization (think of Gradient Descent) among others. Do you study Computer Science or something related to Mathematics/Statistics?
@@rolandlochli4492 I have written this reply so many times, but it keeps being deleted, and I don't know why.
Anyway, I am also studying machine learning (my end goal is computer vision). I am taking a machine learning course right now, and I realized that ML is just statistics with optimization and some advanced linear algebra! So, I was looking for a statistics course to take after this one, but I only found this one from Mit [18.650 | Fall 2016 | Undergraduate]. What do you think? Is it a good choice to take after this one? I am self-studying the field, so ...
Love each and every one of these lectures by Chris!
Every time that I think it’s couldn’t be better I just encounter with another amazing lecture by Chris 👌👍😎
Hope to see more from him 🙏 (especially programming methodology !!)
Awesome feedback, thanks for your comment!
I think the convolution part uses wrong notation f(X+Y=a) = integral (f(X=a-y)f(Y=y)dy), because obviously here there are 3 functions f, one for random variable A=X+Y, one for X and the other Y. All of them are represented by f
Because X+Y = A (a constant) , whatever value X takes, Y is A-X (or the other way)