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Enable fund long term jobs: https://www.patreon.com/3blue1brown
Exclusive thanks to these supporters: http://3b1b.co/nn2-many thanks
Penned/interactive form of this collection: https://www.3blue1brown.com/topics/neural-networks
This movie was supported by Amplify Associates.
For any early-stage ML startup founders, Amplify Companions would appreciate to hear from you via 3blue1brown@amplifypartners.com
To master more, I highly suggest the e-book by Michael Nielsen
http://neuralnetworksanddeeplearning.com/
The guide walks by the code driving the instance in these movies, which you can uncover below:
https://github.com/mnielsen/neural-networks-and-deep-mastering
Also test out Chris Olah’s site:
http://colah.github.io/
His submit on Neural networks and topology is individual beautiful, but actually all of the things there is wonderful.
And if you like that, you’ll *appreciate* the publications at distill:
https://distill.pub/
For far more video clips, Welch Labs also has some great series on machine learning:
“But I’ve by now voraciously consumed Nielsen’s, Olah’s and Welch’s operates”, I listen to you say. Properly nicely, glimpse at you then. That becoming the case, I may endorse that you carry on on with the guide “Deep Discovering” by Goodfellow, Bengio, and Courville.
Many thanks to Lisha Li (@lishali88) for her contributions at the close, and for allowing me pick her brain so substantially about the substance. In this article are the posts she referenced at the close:
https://arxiv.org/ab muscles/1611.03530
https://arxiv.org/abs/1706.05394
https://arxiv.org/abs/1412.0233
New music by Vincent Rubinetti:
https://vincerubinetti.bandcamp.com/album/the-new music-of-3blue1brown
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Online video timeline
:00 – Introduction
:30 – Recap
1:49 – Applying coaching info
3:01 – Expense capabilities
6:55 – Gradient descent
11:18 – Extra on gradient vectors
12:19 – Gradient descent recap
13:01 – Analyzing the network
16:37 – Finding out much more
17:38 – Lisha Li interview
19:58 – Closing thoughts
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