Ah so basically we took the user-item vectors, concatenate them with other variables and put them through neural network.
“How many times are deprecating comments made toward the main character”
Personal preference: High
Average user preference: Neutral
People have asked this question earlier and have NN-ed Movie recommendations, but matrix factorization techniques are still used in production at places such as Netflix, Amazon and MSFT.
Jeremy and his excel skills are exceptional
Wonder If he can teach us that also…
Are there any good collab filtering datasets that we can work on/explore?
Right. I wonder how nns compare to the classical matrix factorization methods?
The Amazon review dataset is an interesting one. Could even do some NLP on written reviews to determine sentiment to add in as s feature.
please also check movieLens, LastFM and jester.
PS : Jester is a joke recommendation dataset.
In the case of NN collaborative filtering, how would you do the exploration phase ?
Movies dataset https://www.kaggle.com/rounakbanik/the-movies-dataset
That’s a good question. I’d probably spend a little time getting familiar with the data itself (missing values, what the variables are, etc.), then try to wrangle it into a format very similar to today’s lecture. Then I’d try to follow along with Jeremy’s example (I’d use the fastai abstractions!)
How would you approach it?
I prefer these ones(short and concise)
Regarding Jacobian and Hessian: I like how they are described in the Deep Learning book. See section 4.3.1 (page 84) here: http://www.deeplearningbook.org/contents/numerical.html
Some good resources on backpropagation:
Backpropagation as a chain rule by Chris Olah: http://colah.github.io/posts/2015-08-Backprop/
Another explanation about the chain rule from Andrej Karpathy: http://cs231n.github.io/optimization-2/
Why you should understand backpropagation: https://medium.com/@karpathy/yes-you-should-understand-backprop-e2f06eab496b
lr is provided by us. can we control da in de/da ? or does pytorch figure that out ?
Can someone please share intuitive Jacobian and Hessian matrix explanation with how they are calculated. Thanks