Over the past decade I’ve written more Google Analytics API queries than I can remember. Initially, I favoured PHP for these (and still do for permanent web-based applications utilising GA...
If you’re not fortunate enough to have a really powerful data science workstation for your work, one of the problems you’ll likely face is that your models can take quite...
The scikit-learn package comes with a range of small built-in toy datasets that are ideal for using in test projects and applications. As they’re part of the scikit-learn package, you...
Regular expressions are used for pattern matching in programming, allowing you to identify or extract very specific pieces of text from a string or document. They’re very powerful and extremely...
When you’re building a machine learning model, the feature engineering step is often the most important. From your initial small batch of features, the clever use of maths and stats...
As a practical demonstration of how the confusion matrix works, lets load up the Wisconsin Breast Cancer dataset, create a classification model and examine the confusion matrix to see how...
As models require numeric data and don’t like NaN, null, or inf values, if you find these within your dataset you’ll need to deal with them before passing the data...
When dealing with temporal or time series data, the dates themselves often yield information that can vastly improve the performance of your model. However, to get the best from these...
When you use pip to install Python packages from The Python Package Index (PyPi) they get stored in your site-packages directory and are used across your system whenever you run...
