Tagneural networks

Python, neural networks and the value of failure

Remember that in my last post about neural networks, I tried (and failed) to replicate the results I obtained in R using Python.

I have been thinking about how I would solve the problem, and frankly I wasn’t eager to spent too much time on such a silly example, especially since I’m not a specialist of the PyBrain module.

The problem is, beside my occasional laziness when it comes to solving problems, I’m also quite stubborn and I don’t like to let things go that easily.

And I realized that it was a great opportunity to write about failure, and how to react when confronted to it.
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Playing around with neural networks – Python version

In my last post I said that I would try to replicate the code in Python. Well here it is.

It is a first attempt, and unfortunately the predictive power of the network thus created is awful (it’s even worst than a random guess…). I need to explore more deeply the options of the module in order to understand where lies the difference between the network created in R and this one.
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Playing around with neural networks and R

I was recently confronted through my work to a classification problem : given a set of explanatory variables, which category a player will most likely end up in (I work in the videogame industry).

To be frank, my statistical knowledge was a little rusty since I have been doing web-dev for a year (unfortunatly stats are not like riding a bike : you do forget after a while). So I ended up doing a quick litterature review in order to list the tools that could help me with this task.

I began with a logistic regression but wasn’t that happy with the accuracy of the result and the implementation was not that easy due to the high volume of data I was dealing with.

Through my readings, I came in contact with various techniques of machine learning and was eager to try them out. I’ve heard about it in the paste but it seemed like a mystical and out of reach corner of computer and information sciences.

And I was wrong. It’s accessible, it works and it’s a lot of fun (well, data-scientist-kinda-fun). What follows is my naive attempt at solving a problem that puzzled me for a while somehow : automatic shape recognition. I mean, how long did it took us as kids to be able to put those damn educational toys into the rightly shaped slot ? Well, quite a long time after all…
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