Good thing about this article is how it breaks down all the steps, I was surprised.
And a very interesting application of NNMF, didn't know it took so long to process the data (but then again, Matlab is usually slow)
Decomposing the Human Palate with Matrix Factorization
11–20 of 21 posts
Re: Decomposing the Human Palate with Matrix Factorization
#12I find this deeply depressing: "the most heavily studied problem in computer science: how to get people to buy more things".
I don't find it depressing at all. I find it empowering. It's the vehicle we use to drive technological progress. We've figured out ways to have people voluntarily give us money to drive technological progress, and so far this has been phenomenally successful. I was just thinking this morning about NASA's use of AWS to crunch data. That was driven by Amazon's ability to get people to buy more things.
Re: Decomposing the Human Palate with Matrix Factorization
#13Since our actual sense of taste is composed of 5 degrees of freedom (1 sour receptor, ~30 bitter receptors, 1 umami receptor, 1 sweet recetor, and 1-3 salty receptors) I wonder how this analysis is then factored in. As other commentators have noticed, tasting is very much a social and visual sensation (olfaction is also huge, try tasting jelly beans while pinching your nose, it's like wax). Perhaps a method to further break the foods down into recipe ingredients and then compare would be beneficial to further categorize taste. You may find that some people don't have certain receptors (many people lack all 30 bitter receptors) and that foods that have these compounds are under represented in the data.
Still, great walk through, it was frank and I loved it!
Re: Decomposing the Human Palate with Matrix Factorization
#14I find this deeply depressing: "the most heavily studied problem in computer science: how to get people to buy more things".
I don't find it depressing at all. I find it empowering. It's the vehicle we use to drive technological progress. We've figured out ways to have people voluntarily give us money to drive technological progress, and so far this has been phenomenally successful. I was just thinking this morning about NASA's use of AWS to crunch data. That was driven by Amazon's ability to get people to buy more things.
This is like saying we should create more government beauracy , because the software and computing tools companies will build to deal with it will in the end get us to Mars faster.
Re: Decomposing the Human Palate with Matrix Factorization
#15Interesting take. I find the categorization around 'other foods' interesting, if not particularly novel. If there's anyone hanging around this board interested in applying machine learning and data science techniques to human sensory data... my company[1] builds flavor profiling and quality control tools for the craft beverage industry. Hit me up[2]!
[1] www.Gastrograph.com [2] JasonCEC [at] ^above url
Re: Decomposing the Human Palate with Matrix Factorization
#16> In other words, matrix factorization is the real deal. It’s the stuff that separates true data scientists from charlatans — the data alchemists, data phrenologists, and data astrologers of the world I certainly hope this is sarcasm. Matrix factorization is, like, the go-to tool for people that don't know anything about what they are studying (i.e. it's the phrenologist's favorite weapon). Factor a matrix, throw the…
SVDs are as basic as hash-tables are to programming.
That would probably be the second thing people learn right after learning how to do some basic regression analysis.
Re: Decomposing the Human Palate with Matrix Factorization
#17> In other words, matrix factorization is the real deal. It’s the stuff that separates true data scientists from charlatans — the data alchemists, data phrenologists, and data astrologers of the world I certainly hope this is sarcasm. Matrix factorization is, like, the go-to tool for people that don't know anything about what they are studying (i.e. it's the phrenologist's favorite weapon). Factor a matrix, throw the…
I have a running joke with my machine learning friends that I will write a Data Science/ML book titled "A Thousand Ways to Say 'Singular Value Decomposition'". The number of papers and techniques out there that are SVD with a few minor tweaks and a unique philosophical interpretation of SVD is hilarious. Here are some examples: Principal Component Analysis - SVD does dimensionality reduction where some n% of variance…
NMF != SVD.
Re: Decomposing the Human Palate with Matrix Factorization
#18Earlier quoted context omitted.
I have a running joke with my machine learning friends that I will write a Data Science/ML book titled "A Thousand Ways to Say 'Singular Value Decomposition'". The number of papers and techniques out there that are SVD with a few minor tweaks and a unique philosophical interpretation of SVD is hilarious. Here are some examples: Principal Component Analysis - SVD does dimensionality reduction where some n% of variance…
> One layer Autoencoder - SVD done by a neural network Not necessarily. Any serious user of autoencoders would apply some kind of L1 regularization or other sparsity constraint to the coefficients learned, so that the autoencoder does not learn the principal components of the data but instead learns an analogous sparse decomposition of the data (with the assumption that sparse representations have better generalizati…
I'd also add here that you can add other variables in to the mix such as gaussian noise and drop out which is the basis for a lot of fundamental neural networks. I get the intent, but it's not necessarily the case.
Neural word embeddings are one of the most fun things I work with. Both word2vec as well as glove and paragraph vectors.
There's also the ability to learn varying length windows of phrases via recursive or convolutional methods.
Re: Decomposing the Human Palate with Matrix Factorization
#19I tried looking for "carbonara", meaning this dish [1]. There are 5 different results, and I believe that all of them refer to the same dish (+/- small variations). However their taste compositions are strongly different. Maybe a little bit of clustering at recipe-name level could improve the result.
Re: Decomposing the Human Palate with Matrix Factorization
#20> In other words, matrix factorization is the real deal. It’s the stuff that separates true data scientists from charlatans — the data alchemists, data phrenologists, and data astrologers of the world I certainly hope this is sarcasm. Matrix factorization is, like, the go-to tool for people that don't know anything about what they are studying (i.e. it's the phrenologist's favorite weapon). Factor a matrix, throw the…
I have a running joke with my machine learning friends that I will write a Data Science/ML book titled "A Thousand Ways to Say 'Singular Value Decomposition'". The number of papers and techniques out there that are SVD with a few minor tweaks and a unique philosophical interpretation of SVD is hilarious. Here are some examples: Principal Component Analysis - SVD does dimensionality reduction where some n% of variance…
Nota bene, for anyone having trouble parsing Homunculiheaded's description of each algorithm: s/interrupt/interpret