Yes you should understand backprop
When we offered CS231n (Deep Learning class) at Stanford, we intentionally designed the programming assignments to include explicit calculations involved in backprop...
Similar Articles (10 found)
🔍 100.0% similar
Yes you should understand backprop
When we offered CS231n (Deep Learning class) at Stanford, we intentionally designed the programming assignments to ...
🔍 70.7% similar
First, thanks to the publisher and authors for making this freely available!
I retired recently after using neural networks since the 1980s. I still s...
🔍 65.9% similar
A Recipe for Training Neural Networks
Some few weeks ago I posted a tweet on “the most common neural net mistakes”, listing a few common gotchas relat...
🔍 62.4% similar
This article doesn't talk much about testing or getting training data. It seems like that part is key.
For code that you think you understand, it's be...
🔍 60.2% similar
Software 2.0
I sometimes see people refer to neural networks as just “another tool in your machine learning toolbox”. They have some pros and cons, th...
🔍 59.8% similar
Deep Neural Nets: 33 years ago and 33 years from now
The Yann LeCun et al. (1989) paper Backpropagation Applied to Handwritten Zip Code Recognition is...
🔍 59.6% similar
Does the Bitter Lesson Have Limits?
Recently, “the bitter lesson” is having a moment. Coined in an essay by Rich Sutton, the bitter lesson is that, “g...
🔍 58.9% similar
Deep Reinforcement Learning: Pong from Pixels
This is a long overdue blog post on Reinforcement Learning (RL). RL is hot! You may have noticed that co...
🔍 58.2% similar
Writing an LLM from scratch, part 22 -- finally training our LLM!
This post wraps up my notes on chapter 5 of Sebastian Raschka's book "Build a Large ...
🔍 57.2% similar
2/3/22, 9:31 PM The Bitter Lesson
The Bitter Lesson
Rich Sutton
March 13, 2019
The biggest lesson that can be read from 70 years of AI research is tha...