Out of what feels like two dozen tutorials and explanations i found this is actually what made me understand it
@OliverJanShD
2 жыл бұрын
This is amazing! Thank you for providing this approach, it really helped me understand GPR a lot better
@youngzproduction7498
Жыл бұрын
This is a solid gold for me. I like learning anything in a visual way which I can interact with it. Thanks for your effort.
@TaylorSparks
2 жыл бұрын
underrated video! Thanks for making this great content. This helped me quite a bit as I prepared a lecture on this topic for my materials science students.
@nicolaipalm7563
2 жыл бұрын
Thanks! Glad I could help you 🤓
@ross302ci
2 жыл бұрын
Extremely helpful for understanding GPRs, thank you!
@muhammadrayyan4389
2 жыл бұрын
You are amazing!!!....thanks for helping me in studying for my Green Light meeting which is due in less than 2 days!!!!..this video gave me a great confidence!!!!...once again thank you very much!!!!!
@satadrudas3675
2 жыл бұрын
This is so underrated. Good job anyway
@ebrahimfeghhi1777
7 күн бұрын
Great video, thank you!
@33gbm
Жыл бұрын
Excellent material you provided here; I just came back to the video to congratulate your efforts on the content hahaha Thank you, man!
@umutkorkut8555
2 жыл бұрын
Very cool and easily digestible content, loved it!
@eva__4380
Жыл бұрын
This was really helpfull for me in understanding GP thankyou so much for your efforts
@pouyaaghaeipour8336
2 жыл бұрын
Can we have access to the notebook file?
@amothe83
2 жыл бұрын
Excellent , the best video on gaussian process regressors
@azd.zayoud
2 жыл бұрын
Well done! # Writing comments would be helpful for beginners if it is put in a context of solving a problem/examples : it will be more useful. Thanks!
@brendarang7052
2 жыл бұрын
Nice one! Thank you.
@swisscheese9590
2 жыл бұрын
Great video. Would you do a follow-up on hyperparameter optimization using marginal log-likelihood in the loss function? Also, a visualization example using multi-input GPs would be interesting as well. Or multi-output GPs.
@NamNguyen.ee2
3 ай бұрын
Thank you so much!
@komuna5984
Жыл бұрын
Absolutely Mindblowing Work! Keep it up. May Allah bless you. 🙂
@erniwidyawati6254
18 күн бұрын
Can you suggest how to do GPR with poisson likelihood? Should i use approximation for inference like using laplace approximation?
@amalroymurali3457
2 жыл бұрын
Excellent stuff. Thanks!
@jaimesastre6393
2 жыл бұрын
Amazing 👌🙏👌 Access to the notebook would be great 🙏🙏🙏
@nicolaipalm7563
2 жыл бұрын
thanks! 😀 link to the notebook is in the description
@icoop99
Жыл бұрын
Very nice video - thank you very much :D
@kaushikgupta1410
2 жыл бұрын
thanks for this amazing explanation
@farhadazadi
11 ай бұрын
This was fantastic
@IvanStar96
2 жыл бұрын
Is sigma 0 or 1 in this example? The title of the graph says it is 0, but doesn't the code say it equals 1?
@nicolaipalm7563
2 жыл бұрын
Yes that is correct. 😀
@fatismajli2490
2 жыл бұрын
Nice Video!
@MrSchwede91
2 жыл бұрын
Kommt die Fortsetzung noch? Bisher alles sehr gut beschrieben...
@junaidlatif2881
2 жыл бұрын
Can we use your method on our data?
@paretos-com
2 жыл бұрын
sure! What kind of data is it?
@yeshuip
2 жыл бұрын
hello, how to feed sequence of input data to train sequences of outputs
@nicolaipalm7563
2 жыл бұрын
With this framework you can feed multidimensional input to the GPR. In order to obtain multi dimensional output you simply train a GPR for each component of the output vector. :)
@yeshuip
2 жыл бұрын
@@nicolaipalm7563 thanks for the reply. but my question was is it possible to feed N*d matrix as input and N*2 aa output. where N represents the input sequence and d represents dimension of features and N as output sequence number and 2 as number of output features
Пікірлер: 35