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#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.

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The Blog Post of Matt Mazur : https://mattmazur.com/2015/03/17/a-step-by-step-backpropagation-example/?fbclid=IwAR1IcdSd6vAohn1CMLILd6lu7C5aMrY6T37H6Wmf4Xean6DSI7hAX8Vk9eQ

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38 Comments

  1. 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.

  2. If you don’t mind quick question:

    So the model Can be plugged into all my data sets correct? Im on Azure and from what I can make out thats what will need to happen to get what I need which is results from visual data and the mechanical data.

    Ball park??

    Thanks in advance

  3. I spent one month reading books to understand how it works as I'm bigginer and thanks to that video I got the concept in 15mn. very good job, keep on
    looking forward to learn more and apply it real world problem

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

  5. 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.

  6. Thank you very much for this great video! I have watched a lot of videos before finally landing on this video. Unfortunately all others have seemed to just shy away from explaining the real math behind back-propagation. They just cover the basic idea or update the weight for the output layer only. This is the first video I have seen that explains the actual math in updating the hidden layers too.

  7. La partie simple du problème est longuement & bien expliqué , mais la backward propagation c'est vite fait mal fait. Comme si tu n'avais pas toi même compris la problématique. Tu m'as m'as plus induit en erreur qu'autre chose …

  8. In back propagation you didn't update the bias weights. Do they stay constant throughout the whole training?

  9. The forward propagation is well explained but the backpropagation isn^t. The example has errors.

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

  11. There is at least one mistake, but as overall how its work is quite good presented. In sake of correctness you should check number once again. In w dIno2 / dW8 you wrote 0.61 but in dEtotal /dW8 you wrote 0.52. Best regards

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

  13. 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" ?

  14. could you please explain why you did not update the biases and how the biases are updated in back propagation?

  15. J'ai manqué un épisode ou quoi ?!
    De l'anglais !!!
    🤔Dois-je peut-être m'abonner aux chaînes de geek qui ont encore le Français comme langue de diffusion ?

  16. non mais non ! ! le but de ce sujet est complètement rater…. y'a presque pas de vidéo en français sur le sujet et y'as en des milliard en anglais !!!! fait le en français mon ami

  17. Pourquoi lors du calcul du "nouveau poids" on multiplie la dérivée par 0.80? Merci

  18. 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 output_produced-desired_output) 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😊😊

  19. The numbers don't add up. From the graph :

    (j1 = i1. w1 + i2.w2+b1)

    'w2' corresponds to 0.13 and not 0.25.
    0.25 appended to w3, as shown in the graph.

    w5 is 0.67 and not 0.84! I have a lot of trouble understanding.

  20. Salut, je crois qu'il y a juste une petite erreur sur ta diapo lorsque tu récupères la dérivée partielle de Etotal par rapport à W8. OutJ2 est de 0,61 or dans le calcul il a la valeur de W8 soit 0,52. Peut-être une incompréhension de ma part, sinon super vidéo même en anglais ! 🙂

  21. petite question pour le learning rate qui est de 0,8 dans la formule, tu l'a choisi par défaut ou tu l'a calculé plus tôt?

  22. 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.

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