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Using Machine Learning and Node.js to detect the gender of Instagram Users

totems.co

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Re: Using Machine Learning and Node.js to detect the gender of Instagram Users

#41

Post by spolu »

im3w1l wrote: post #38

Your implementation of momentum seems off, you just add a multiple of last error, instead of adding exponentially declining contributions from the past. I think you want double dW = alpha_ * val_[l][j] * D_[l+1][i] + beta_ * dW_[l+1][i][j]; W_[l+1][i][j] += dW; If you want to get an output class probability, softmax is the standard way. Minimize KL-divergence instead of squared error. You don't seem to be doing any r…

> Your implementation of momentum seems off

I think we used what is described in Artificial Intelligence: A Modern Approach... But I have to check because what you propose seems better.

> If you want to get an output class probability, softmax is the standard way. Minimize KL-divergence instead of squared error.

Thanks! We'll totally try that.

> You don't seem to be doing any regularization. It could maybe give you better generalization.

Thanks again. Someone mentioned that before as well. We'll have to experiment with that as well.

> Training on multiple threads and averaging is a nice touch. It would be interesting to hear if (how much) it improved your results.

Training was much faster and therefore tractable on a much larger set but we didn't manage to get our best results using this multi-threaded approach unfortunately as described in the post.

Maybe with a bigger training set we could have reach better results using multi-threaded training. That being said, the averaging phase disrupts a lot the overall backpropagation process, so I don't know how efficient it can be... Some advanced experimentation would probably be interesting here.

Re: Using Machine Learning and Node.js to detect the gender of Instagram Users

#44

Post by barsonme »

needacig wrote: post #28
gstar wrote: post #2

It's unusual to see a coherent, from-first-principles explanation of a neural network. Especially one that's commercially valuable (i presume) to Totems. Mildly alarmed to learn I'm only .039 probability male, though - better bloke it up on Instagram.

What's so alarming about being thought female?

Personally, being male, I'd rather be thought of as male. Not as a slight towards females, but just because it's who I am.

That said, I did get 0.998 female and 0.996 male. Oh well.

Re: Using Machine Learning and Node.js to detect the gender of Instagram Users

#45

Post by flashman »

spolu wrote: post #23
adelevie wrote: post #20

This is a great example of how privacy is not optional, even in "opt-in" systems such as Instagram and FB. That Instagram does not require you to have a Facebook profile, and Facebook does not require you to list gender means very little in terms of your own privacy. Merely choosing to withhold information about yourself does not insulate you from a breach of privacy. That others do disclose such information allows 3…

> There's a strange morality here: at what point is it unethical to voluntary disclose data about oneself That's an interesting question. Especially since the data you disclose may triggers inappropriate inference of characteristics on someone else, maybe eventually causing some form of harm (anytime the demo fails to classify someone, we do cause some harm to him/her in a way). In the case where the misclassificatio…

In other words: how am I affected by the fact that many of my Facebook friends like drug-related pages?

Re: Using Machine Learning and Node.js to detect the gender of Instagram Users

#46

Post by syldor »

It's true that it seems to be a lot of work in implementation. NN have a complexity/performance ratio much higher than other algorithms. But hey ! la fin justifie les moyens, I'm quite impressed with the result and had a lot of fun with the demo and the article. Keep it up guys !

Re: Using Machine Learning and Node.js to detect the gender of Instagram Users

#47

Post by muglug »

plg wrote: post #39

@teganandsara PROBABILITY FEMALE: 0.003 PROBABILITY MALE: 0.996 I would say this doesn't work very well.

Well, one datapoint means nothing. Also, if this is aimed at advertisers, it's more useful to identify people whose interests skew (stereotypically) male or female.

Also, Tegan and Sara are great singers and artists, but neither of them is an exemplification of what our culture considers stereotypically female.

Re: Using Machine Learning and Node.js to detect the gender of Instagram Users

#48

Post by hnriot »

adelevie wrote: post #20

This is a great example of how privacy is not optional, even in "opt-in" systems such as Instagram and FB. That Instagram does not require you to have a Facebook profile, and Facebook does not require you to list gender means very little in terms of your own privacy. Merely choosing to withhold information about yourself does not insulate you from a breach of privacy. That others do disclose such information allows 3…

I don't get your point. If you post online do you really expect much privacy? Make your profile private and then the software won't be able to guess your gender. I tried three accounts, one was of a famous female model and apparently she's 0.516 probably male and 0.006 female, so I wouldn't be too worried just yet. Just don't post online if you want privacy, otherwise, learn from this.

Re: Using Machine Learning and Node.js to detect the gender of Instagram Users

#50

Post by spolu »

syldor wrote: post #46

It's true that it seems to be a lot of work in implementation. NN have a complexity/performance ratio much higher than other algorithms. But hey ! la fin justifie les moyens, I'm quite impressed with the result and had a lot of fun with the demo and the article. Keep it up guys !

:+1:
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