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skew

Machine learning feup second assignment. Cs231n fully connected nets assignment 2. Cs231n neural net assignment. Machine learning intro assignment FEUP. Functions of a random variable.

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Machine learning feup second assignment. Cs231n fully connected nets assignment 2. Cs231n neural net assignment. Machine learning intro assignment FEUP. Functions of a random variable.
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skew | nunoskew.github.io Reviews

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Machine learning feup second assignment. Cs231n fully connected nets assignment 2. Cs231n neural net assignment. Machine learning intro assignment FEUP. Functions of a random variable.

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skew

https://nunoskew.github.io/functions-random-variable

September 3, 2014. The goal of this post is to come up a way to derive the p.d.f of a function of a random variable. The big picture of functions of random variables is this:. A lot going on in this figure . We have seen in a previous post. That a random variable is actually a function the maps outcomes into something else. Now we have some other function that maps the values of the random variable into something else! And if there are several ’s such that then we should sum their probabilities!

2

skew

https://nunoskew.github.io/untitled-01

June 16, 2016. Yo, that’s deep.but what about this:. Begin{equation} label{eq:1} omega = d phi / dt end{equation}. Aw ( ref{eq:1}) is a differentiation.

3

skew

https://nunoskew.github.io/negative-binomial-distribution

October 19, 2014. This will be a quick post about the not so well known Negative Binomial Distribution. This distribution models the following quantity:. Let be a Bernoulli random variable with parameter . The number of failures before. Successes is a random variable that follows the binomial distribution! It has the following p.f. So how many combinations are there? We’re essentially sampling with replacement until a fixed number of successes! So the m.g.f. of the negative binomial is:.

4

skew

https://nunoskew.github.io/poisson-distribution

October 20, 2014. Now comes the stroke of genius. As he doesn’t really like the formula of the p.f. of the binomial distribution, he tries to come up with another one. Here’s how he does it:. So it seems like. Now, to make this a probability distribution, it has to sum up to 1! This last function is the probability function of what it’s known by the Poisson Distribution. This guy really shouldn’t be a shop owner. Note the two major assumptions. Now lets check its attributes:. If you can come up with an e...

5

skew

https://nunoskew.github.io/moments

October 21, 2014. Today i’m going to talk very quickly about a very strange piece of math called the M. Unction(m.g.f.)! And by this I mean a function that generates moments D:! Http:/ www.youtube.com/watch? So, what are moments! Moments are associated with a random variable, and consequently, with its distribution. The kth moment of a random variable is this:. It is the expectation of the kth power of the random variable . There are also central moments! So, the next question would be: Ok, but what now?

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nunoskew (Nuno Marques) · GitHub

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Http:/ nunoskew.github.io. Oct 9, 2013. Deep Learning library for Python. Convnets, recurrent neural networks, and more. Runs on Theano and TensorFlow. Check the full story in http:/ ajourneyintodatascience.com/neural-networks-beginners-edition. A simple Jekyll theme for showcasing your work, emphasis on whitespace, transparency, and helvetica. Recurrent Neural Network - A curated list of resources dedicated to RNN. 19 contributions in the last year. Nunoskew has no activity during this period.

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I did my BSc and MSc in Computer Science at University of Porto. In my MSc i specialized in Data Mining, so that led into competing in some machine learning kaggle competitions. As my results were far from what i wanted, my interests in machine learning/data science began to grow and nowadays i want to make a career out of it! So if you’re interested, be sure to check it. I’ll also be uploading my code in my github account. If you do too, pm me for some games :). 2015 / proudly powered by WordPress.

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Machine learning feup second assignment. Cs231n fully connected nets assignment 2. Cs231n neural net assignment. Machine learning intro assignment FEUP. Functions of a random variable.

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