In the field of Machine Learning there are multiple models whose internal structure makes it non-trivial to understand the why behind the decisions it makes. This set of models are widely known as black box models and are usually very…
Imagine you are a data scientist working for a company that has decided to merge the databases of two of its departments into one. There is no common index between the two sources and the task is to ‘deduplicate’ the…
The pricing systems currently used in companies have a substantial difference with respect to those of 20 years ago. We have moved from static pricing systems, that is, constant prices at different times of the year, to dynamic systems, where…
This post will deal from another point of view with one of the most popular games that can be played on paper, the Sudoku. The objective will be to explain an algorithm for solving it, together with the code that…
Modeling and explaining the consumer behavior of a product is very important to know what factors affect their behavior, price being one of these important factors. Let’s take as an example a company X that sells clothing. It is a…
A linear regression is a model that is used to approximate the linear relationship between a dependent variable Y and a set of independent variables X. In matrix format it can be expressed as where ε is a vector of…
Introduction All graphics in this article are interactive due to the nature of trying to represent text graphically. To see which sentence each point represents, simply hover the mouse over it. The results obtained have been generated on the “STS…
What is a digital twin? When we talk about digital twins, we are mainly referring to a virtual representation of a physical system, where a copy (twin) of the real environment is reproduced using the information (Big Data) that affects…
The kernel trick is a typical method in machine learning to transform data from an original space to an arbitrary Hilbert space, usually of higher dimensions, where they are more easily separable (ideally, linearly separable). This technique is the basis…
A few weeks ago, we talked in our blog about Object recognition with Deep Learning, explaining this technique and some of its algorithms. In this post, we will analyze a very similar area known as semantic image segmentation, a computer…