Caching is really useful but can be a bit of a pain to set up when you’re also using blueprints in your Flask App.
Simple linear regression is the process of identifying the linear function (non-vertical straight line) which best describes the relationship between one independent and one dependent variable.
Factorising an equation is the reverse procedure to expanding brackets. It’s GCSE level math and is definitely something most people who use math on a regular basis should be able to do.
Differentiation is the process of computing the gradient (derivative) of an arbitrary function and can be used in many simple cases to minimise a function describing the loss (error) of our model.
Sometimes mathematical notation can seem a bit opaque, to the point where the mathematical notation used in a paper is usually noted at the beginning of the text. These are the relevant ones for the math I’ve used.
In order to effectively evaluate our models we need something to evaluate them with. To achieve this we split our data into three groups: Training, Validation and Evaluation…
If it can take on different values, it’s a variable. They come in a variety of flavours and are extremely important in experimental design.
A very small chunk of Bash to fix broken virtualenv symlinks.
There are two ways to add non-standard fonts to WeasyPrint pdfs: the ‘normal’ css way: by installing a local copy and using
@font-faceor by adding the remote stylesheet to your stylesheet list when calling
A confusion matrix is a simple way to visually present the accuracy of a classification algorithm.
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