Product matching (or data matching) is a computational technique employing Natural Language Processing, machine learning, or deep learning, which aims to identify identical products being sold on different websites, where...
If you’re working in data science, and especially if you’re working in deep learning, you’re going to need a decent workstation in order to be productive. Earlier this year I...
Heatmaps are one of the most intuitive ways to display data across two dimensions, and they work particularly well on temporal data, such as web analytics metrics. They’re a great...
Recent papers on the Recency, Frequency, Monetary or RFM model, such as the one by Inanc Kabasakal in 2020, have started to adopt text-based labels to help people understand the...
Scatterplots, scatter graphs, scatter charts, or scattergrams, are one of the most popular mathematical plots and represent one of the best ways to visualise the relationship of data on two...
During the Exploratory Data Analysis or EDA stage one of the key things you’ll want to do is understand the statistical distribution of your data. Histograms are one of the...
The boxplot, or box-and-whisker diagram, is one of the most useful ways to visualise statistical distributions in data. While they can seem a bit unintuitive when you first look at...
Imbalanced classification problems, such as the detection of fraudulent card payments, represent a significant challenge for machine learning models. When the target class, such as fraudulent transactions, makes up such...
Something which often confuses non data scientists is that too many features can be a bad thing for a model. It does sound logical that including more features and data...
