Backpropagation explained | Part 1 - The intuition

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Let's discuss backpropagation and what its role is in the training process of a neural network. We're going to start out by first going over a quick recap of some of the points about Stochastic Gradient Descent that we learned in previous videos. Then, we're going to talk about where backpropagation comes into the picture, and we'll then spend the majority of our time discussing the intuition behind what backpropagation is actually doing.

We're going to be building on concepts that we covered in a couple of previous videos. These two videos covered what it means to train an artificial neural network, and how a network learns. So if you haven't seen those yet, go ahead and check them out now, and then come back to this video once you finish up there:

🕒🦎 VIDEO SECTIONS 🦎🕒

00:20 Agenda
01:20 Recap stochastic gradient descent (SGD)
04:40 Backpropagation intuition
08:28 Backpropagation summary
10:19 Collective Intelligence and the DEEPLIZARD HIVEMIND

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This video deserves to be on television at dinner time.

danluba
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this course is so nice you are simplifying complex ideas in a really nice way, I think this series should be binge watched like a netflix series to refresh your memory on all these concepts XD

husseinwassouf
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your videos are actually great in expressing the concepts in possibly quickest time . i havnt seen your other playlists yet. but this one really helped me so much.

maedehzarvandi
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I have just completed watching all the 27 videos in the list. All are excellent videos!! Thanks for uploading. Please continue the good work!! Thanks!

parthasarathybalaraman
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00:00 Intro
01:23 Recap stochastic gradient descent (SGD)
04:42 What is backpropagation, the intuition
08:28 Summary

GirlKnowsTech
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Backpropagation explained | Part 1 - The intuition

Backpropagation explained | Part 2 - The mathematical notation

Backpropagation explained | Part 3 - Mathematical observations

Backpropagation explained | Part 4 - Calculating the gradient

Backpropagation explained | Part 5 - What puts the “back” in backprop?

Note, at 7:44, I misspoke when I stated that the updated values we get for the weights are the the corresponding derivatives of the loss function with respect to each weight.


deeplizard
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Yes i want to know on the math behind backprop

RaghavendraBoralli
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There is no limit to the awesomeness of her explanation!

justchill
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Thank you very much for this video! It was fantastic that I could finally understand how SGD uses back propagation to calculate the gradients to minus off!

tymothylim
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Just can not THANK YOU enough for this Greatest of videos on the topic. Just Brilliant.

RohanPaul-AI
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after watching many videos on this topic yours was EASILY the most helpful by far. It is accurate, simple, and just all around perfect. the image is very simple. I love your voice and the explanation is so good.

nicholasscotto
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I cannot thank you enough. I don't know how many videos I watched to clear this concept, nothing helped but your video. You explained it in a very detailed and clear way. Thank You so much!

ThePRINCEBARPAGA
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Omg Thank You!
All these books make it so complex and include a bunch of unnecessary equations before a noob like me can actually understand the process.
I am interested in the math as well but first I have to know the concept, otherwise I often find myself understanding these complex details and be like, why exactly are we doing this?
This video actually makes sense and now I can dive deeper into it. Nice animations too. Props to you guys

zw
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Bless you for making the world a better place. Keep up the good work!

hkrishnan
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Thanks you very much for making this great videos. And I want to know more about maths

javierCi
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thank you very much for this clear and helpful explanation.
Words fail to express my gratitude.

qusayhamad
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This is an amazing video and I understand the deep learning instantly!

yzyangliang
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I already know the math behind back propagation; however, I will watch your videos in order to see how you are going to present it. Your way of giving the information is awesome. I want to see how it will work with the math complexity.

mohamedmahdy
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YES YES YES YES YES YES WE NEED MATH TOPICS

ismailelabbassi
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such an awesome super simple explanation! and how you bring up the math, it's almost like a teaser :) now I want to see the Math! =)

richarda
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