#2 BACKPROPAGATION algorithm. How a neural network learn ? A step by step demonstration.

It is my first video in English I hope it is ok. I will start to do on my Youtube channel more expert video in English.

In this first video we details the backpropagation algorithm, really used in Deep Learning to train supervised neural network.

[Tomcatdude]

For anyone in the future trying to look for how todo backprop easily:

For the first set of weights, we use -(expected - given) * (given * (1 - given)) * output of previous node. expected and given in respect to this video would be values using o2 or o1 (depending on which weight you're working on), and output of previous node in this would be output of j2 or j1 (again depending on which weight it's attached to). This is our final gradient, so we can multiply this by the learning rate and subtract that from the weight to get our updated weight.

For the rest of the weights in any hidden layer: We take the two (-(expected - given) * (given * (1 - given))) we just computed in step 1 and multiply them by the two weights they were used to update(so if we're updating w4 we use the two weights connected to j2). We then multiply this by (given * (1 - given)) for the given value after the activation function (so for w4 we'd use the output of j2 for given). Finally, we multiply this by the input the current weight is affecting (so for w4, we'd use i2). This is our final gradient, so we can multiply this by the learning rate and subtract that from the weight to get our updated weight.

[sawmill]

I actually kind of laughed at around 1:38 when he was like "All you need to know is addition, subtraction, multiplication

...

and partial derivatives."

Lol, you really had all those 3rd graders in the first half, not gonna lie.

[colorfularty]

Thanks man! This is the final thing I needed to really put the pieces together and see how backpropagation works!

[Antagon]

After watching your video I was finally able to derive the equation myself .
Thank you!

[Dhanush-zjmf]

I spotted two mistakes but please tell me if I am wrong . At 10:51 "dEo1/d(out o1)" should be "0.80-0" (which is the which evaulates to 0.80 and you wrote "-0.18" in that place so please once check it and tell me if I am wrong😊😊

[sawomirslusarczyk]

in the Compute 02 line in the formula there should be w7 instead of w5 and w8 instead of w6. Regards Slawek

[gabupouet]

C'est vraiment dommage, je suivais cette chaine pour le simple fait que c'était en français. Des trucs en anglais sur le sujet, il y en a par tonne.

[wazmo]

Merci Beaucoup! You really helped me out I was struggling with this for a while 😅

[gauravonkar]

9:06 There should be 0.61 instead of 0.52

[alexandervega]

good explanation helped to understand some inner details from a basic neural network.

[KMegahertz]

At 8:10 I dont follow where the -1 came from. Anyone care to shed some light?

[hosseinebrahimian]

cette video ma bien aide a comprendre BP algorithm. merci a vous!

[PugzNotDrugzEditz]

your (d out j2)/(d inp j2) value at 11:09 is wrong. See at 3:45 the value of sigmoid of j2 is 0.61. If you calculate 0.61(1 - 0.61) you will get 0.2379 instead of what you got 0.16. Please fix that. Its bugs me after calculating for so long my answer is not matching the answer in the video.

[nanobert]

Please can you make a video on support vector machines and ROC AUC

[Emoups]

Bonjour et un grand merci pour la Vidéo, je cherchais un example vulgarisé et c'est parfait.
Concernant les "Bias" est ce que l'on applique aussi une correction ou on ne s'occupe que des "weights" ?

[juliano]

Nice video. More videos on english would be cool :)

[geogeo]

Génial c'est pile que je cherchais, les vidéos sont super propres et claires, en + du contenu en français qui + est ! bravo et merci

[yosimadsu]

No labeling is confusing me with numbers only

[yusrahsumtally]

At 11:13, could you explain how did you get 0.16? just the values

[dmitrysakharnikov]

Thanks for this video, but unfortunately unclear how to update bias values while training.