Google’s PageRank (Sort of) Explained
In this post we’ll take a look at the algorithm which defines Google’s pagerank (PR) analysis. A webpage’s PR is a number between 0 and 10 that Google uses to estimate the usefulness of that page. For example, CNN.com has a PR of 9. A “typical” web site might have a PR of 5. Pages […]
Neural Networks Tutorial, Part #3
In our previous tutorial we’ve laid out the basic form of our two layer feed-forward neural network (FFNN). In this installment we’ll derive a way of training it. Just to remind you, here is the basic outline of our neural network, along with all relevant variables:
In general, when training a network, one prepares a […]
Neural Networks Tutorial, Part #2
A Short Review
In the previous part of our tutorial, I’ve spoken about feed forward neural networks (FFNN), and said that the basic building block of a FFNN is a layer, which can be concisely summarized using the following diagram:
A layer has N inputs and M outputs (schematically represented here by a single line at […]
Neural Networks Tutorial, Part #1
This is the first part of a set of postings on neural networks (NNs). NN are constructs that attempt to mimic our brain’s activity to a degree. NNs have become so common that it’s useful to know what people are talking about, so I’ve decided to write a brief tutorial - in several parts - […]