Tutorials

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Turning Emacs into a helpful Haskell IDE

I imagine I'm like a great many programmers who feel they learn best by just jumping straight into writing some code. The issue with this: I am a lazy programmer and I like to make my development environment do all of the work! And therefore I encounter an issue where if I don't have a smart IDE I start to make huge mistakes that take forever to spot.

Continue reading Haskell-ing in Emacs

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neural-networks-3

 

First off thank you to Stephen Welch who inspired the code examples in this section.

So in part 0 we looked at the general idea of how a Neural Network could work, it's now time to build upon that theory and actually start something cool.

What will this cover?

This article will be covering the basics of setting up a [dumb] neural network. This will be done in Python 3 with the numpy library (if you don't have a working environment set up check out this).

Continue reading Building Neural Networks: Part 1

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mirror_neurons

 

Machine learning is great, it's hip, cool and learning to implement your own is a great learning slogg adventure

So that's what I'm going to do, and I'm going to essentially tutorialise my understanding in neural networks in order to teach anyone interested in how to produce an original example network (examples will be in python 3).

This first entry in the series is going to cover the theory and make sure that it is cemented, before attempting to write any code or analysis any kind of data.

Continue reading Building Neural Networks: Part 0

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