Uploaded November 2020 | Updated September 2026, 1 week ago
The main ideas behind Backpropagation are super simple, but there are tons of details when it comes time to implementing it. This video shows how to optimize three parameters in a Neural Network simultaneously and introduces some Fancy Notation.
NOTE: This StatQuest assumes that you already know the main ideas behind Backpropagation: youtu.be/IN2XmBhILt4
...and that also means you should be familiar with...
Neural Networks: youtu.be/CqOfi41LfDw
The Chain Rule: youtu.be/wl1myxrtQHQ
Gradient Descent: youtu.be/sDv4f4s2SB8
LAST NOTE: When I was researching this 'Quest, I found this page by Sebastian Raschka to be helpful: sebastianraschka.com/faq/docs/backprop-arbitrary.html
For a complete index of all the StatQuest videos, check out:
statquest.org/video-index
If you'd like to support StatQuest, please consider...
Patreon: patreon.com/statquest
...or...
YouTube Membership: youtube.com/channel/UCtYLUTtgS3k1Fg4y5tAhLbw/join
...buying one of my books, a study guide, a t-shirt or hoodie, or a song from the StatQuest store...
statquest.org/statquest-store
...or just donating to StatQuest!
paypal.me/statquest
Lastly, if you want to keep up with me as I research and create new StatQuests, follow me on twitter:
twitter.com/joshuastarmer
0:00 Awesome song and introduction
3:01 Derivatives do not change when we optimize multiple parameters
6:28 Fancy Notation
10:51 Derivatives with respect to two different weights
15:02 Gradient Descent for three parameters
17:19 Fancy Gradient Descent Animation
#StatQuest #NeuralNetworks #Backpropagation
The main ideas behind Backpropagation are super simple, but there are tons of details when it comes time to implementing it. This video shows how to optimize three parameters in a Neural Network simultaneously and introduces some Fancy Notation.
NOTE: This StatQuest assumes that you already know the main ideas behind Backpropagation: youtu.be/IN2XmBhILt4
...and that also means you should be familiar with...
Neural Networks: youtu.be/CqOfi41LfDw
The Chain Rule: youtu.be/wl1myxrtQHQ
Gradient Descent: youtu.be/sDv4f4s2SB8
LAST NOTE: When I was researching this 'Quest, I found this page by Sebastian Raschka to be helpful: sebastianraschka.com/faq/docs/backprop-arbitrary.html
For a complete index of all the StatQuest videos, check out:
statquest.org/video-index
If you'd like to support StatQuest, please consider...
Patreon: patreon.com/statquest
...or...
YouTube Membership: youtube.com/channel/UCtYLUTtgS3k1Fg4y5tAhLbw/join
...buying one of my books, a study guide, a t-shirt or hoodie, or a song from the StatQuest store...
statquest.org/statquest-store
...or just donating to StatQuest!
paypal.me/statquest
Lastly, if you want to keep up with me as I research and create new StatQuests, follow me on twitter:
twitter.com/joshuastarmer
0:00 Awesome song and introduction
3:01 Derivatives do not change when we optimize multiple parameters
6:28 Fancy Notation
10:51 Derivatives with respect to two different weights
15:02 Gradient Descent for three parameters
17:19 Fancy Gradient Descent Animation
#StatQuest #NeuralNetworks #Backpropagation
