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Bayesian Neural Network | Deep Learning

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Nice, I Apply this méthod, much better result, compared tô standard NN
Comment from : @BRunoAWAY

love from wuhan
Comment from : @fujiang9920

Only two minutes in, and I can already say with confidence that this is the best explanation of B-CNN I've ever seen Thanks a lot!
Comment from : @M94-24

Cool video
Comment from : @rajarajankirubanandan3154

Thanks a lot Can you share some of your published papers that I can go through
Comment from : @mohdata100

How do you backprop in Baysian Neural Networks ?
Comment from : @Trubripes

One of the best and most concise descriptions to BNNs for newcomers such as myself
Comment from : @waleedkhan8590

Awesome video!! Nice and clear explanation! It would be perfect if the recording equipment was better👏
Comment from : @RangoKe

Wow this is way better than blog posts!!
Comment from : @phoenix2718Utube

Can we use thembrFor regression problems?
Comment from : @SamiaToor

Very well explained!
Comment from : @liorkissos9303

Bayesian integration estimate
Comment from : @hgmarques

Best explanation on Bayesian neural nets
Comment from : @makamsidhura

Thank you!
Comment from : @jzzzxxx

Top best ever explanation, side by side thus you know how different it is from standard NN
Comment from : @Must23

A future video idea A python example of above
Comment from : @user-wr4yl7tx3w

This is excellent explanation
Comment from : @user-wr4yl7tx3w

Great explanation Simple and to the point
Comment from : @my7username7is

Can you share the example? for a BNN regression problem I need to make a BNN for 06 inputs and 1 output problem thanks
Comment from : @excursion5246

This is one of the best explanations I have seen on Bayesian neural networks Thanks!
Comment from : @sibyjoseplathottam4828

3:55 Here my years of college crept in asking: Why is it equivalent? Doesn't this assume a particular loss function?brbrI'm not quite sure - and perhaps the question is banalbrbrBut thank you very much, the video is incredibly helpful!brbrbrEdit: Sorry I didn't pay attention you mentioned that only some Loss-functions adhere to this criterion ^^brbrIt is so satisfying to feel that those years of statistics finally pay offbrbrThank you very much!
Comment from : @walterreuther1779

What is mean aggregator and burnin in deep learning? Any chance to explain this
Comment from : @1UniverseGames

Thank you for a great video! any references?
Comment from : @Globalian001

Wow soon we'll get machine-generated tickets in the mail for going out without a mask!
Comment from : @ThePeterDislikeShow

Yep, I finally understood it Thanks!
Comment from : @andreymanoshin2202

Provide code or it didn't happen
Comment from : @drmerlot1532

u explained the bayesian nn in the easiest possible way that i can think of excellent work
Comment from : @arjunroyihrpa

wonderful!
Comment from : @jmdvinodjmd

Thank you very much, great video
Comment from : @ConcreteJungle95

This is really helpful So the ensemble is kind of a simplified bayesian ?
Comment from : @canalfishing4622

really helpful
Comment from : @chetansharma4748

its a really helpful video , thanks a lot
Comment from : @faatemehch96

Hi, sorry I don't know much about what was talked about here in the video but I found it intriguing I will be entering college soon and am deciding on my major Is this statistics? Or Computer Science? Or mathematics? Felt like a combination of all of them (all 3 fields are very much overlapping too)
Comment from : @anantsharma7955

I enjoy your videos, and I have a suggestion to improve the audio quality You should build or buy a pop filter to put in front of the microphone to eliminate the puffing sounds This way you can talk even closer to the microphone and the audio will improve
Comment from : @softerseltzer