This is a very clear explanation of the Bayesian Linear Regression. Thank you!

Brown Amy Harris Lisa Garcia Ronald

In your example (8:00) of a hypothetical variogram....I don't get the logic of A correlated to B, B correlated to C but A not correlated to C. Logically speaking: If A is correlated to B then B must also be Correlated to A, and if B is correlated to C then C must also be correlated to A (since B is correlated to C and B is correlated to A)....its a bit of a hurdle in understanding the paradox :-) Thank you so much for posting these lectures....I find them extremely useful.

Awesome video, Thanks! If we have a problem with ML, could we discuss the issue with you?

I love it

One of the best introductory classes I’ve seen, thanks so much. I have a basic (sorry) technical question: you seem to be showing slides from a ppt but inside you have working python notebook. How do you do this?

do you have a video of spatial correlation/auto correlation?

Cool video

Hi sir , could you please interpret the result ? , i am getting some confusion related to the categorical value interpretation from the output

Your classes are amazing!

Thanks! Played with your code for the Gaussian stuff and had an ah-ha moment.

Great explanation!!

Let's say that I'm tracking the profile of some person. I choose features F1, F2, F3, ..., Fn. I designed idiocy function fi. This is a function which maps features in the range between 0 and 100. You say that we need to model the distributions F_x. How I could do it? Do I need to steal this knowledge from somewhere?

Thank you so much!

Excellent explanation and presentation

Best content from best teacher...please continue to share the very interesting contents...following from Algeria :)

great lecture. is it possible to adjust the density values based on cluster density?. is there any algorithm to achieve this?. thanks

Super!

Hi, do you have any Excel file that shows the two-dimensional variogram? Like parallel and perpendicular transects?

Excellent video Professor. May I get access to your PPT slides. Thank you so much for making such amazing lectures open source and accessible.

Thanks a lot ! Very clear explanation

You're awesome! Thanks so much for this.

Thanks great explanation! GeostatsGuy can I ask you what if I have to sample categorical classes. For example, prediction model of land use changes. I would add non-changes but where if i have clustered changes (i.e. changes that occur in one specific region). Thanks!

Thank you Very much!!!

Hi professor, thank you for all your lectures - they are a great resource for fundementals. I wanted to ask, @ 35:24 you speak about creating a 2D ndarrays using the meshgrid function. I wanted to ask why the "-1*" is needed in the arguments for the "yy" array?

Greetings from #China professor. I am honoured to be your virtual student and always feel pleasure in learning from your videos. Keep inspiring!

Thank you Michael for this awesome video!

Is "stationarity" in this lecture similar to "homogeneity"?

The way you explain is fantastic. Thank you for making it available for the public!

Thanks Proffesor for helping us and sharing your knowledge, that was really helpful.

Thanks Pr. Pyrcz

"PromoSM"

Happy New Yr, waiting for DS & ML project end-end. kindly make it

This is absolutely amazing. I took Bayesian stats for my MS in Data Science (Analytics) from Georgia Institute of Technology, a top three engineering school, and yet, even as a top tier engineering school, neither the professor nor the TAs bothered to explain these this well. I will be rewatching this several more times. Thank you for the work you put in to create all of this and talk us through it.

Thank you very much for sharing this outstanding content.

😍 thx for new topic

thank you very much. I enjoyed your interesting presentation.

Nice explanation

Thanks for the very nice demonstration 👍

Thanks as always Mike. I love this short demo series. They are great teasers for deciding what I would like to dig deeper into with your other lectures

When learning about a complex topic, there is a teaching moment when the diverse components make sense together. This video brought disparate parts of my knowledge and experience together brilliantly. I am a software developer who is making the transition from managing financial transactions to analyzing features that explain migration. This video helps me so much. Thank you!!!!

Wooow, thx for video

Amazing.

Awesome! I am loving this series! Thank you!!!

Great stuff, keep it up boss

It's a pleasure to see you again

It's a clear explanation and very helpful. Much appreciated.

Thank you for this, Professor Michael.

is there any section in the courses where you show certain concepts by coding?

What can be the physical interpretation of negative correlation? How is it possible that places dislike each other?, Michał Michalak