In a previous article of our blog we detailed what is RAG (Retrieval Augmented Generation) and how to take advantage of embedding models to extend the knowledge of an LLM with our own document base. In this post, we will…
The linear regression model is one of the most useful tools in every data scientist’s kit bag. Although this post is geared towards people with first-hand knowledge of this statistical model, it never hurts to remember that linear regression aims…
RAG stands for “retrieval augmented generation”. RAG is intended to allow a “large language model” (LLM) to use additional information provided by a user. LLMs are trained on large amounts of text, usually obtained from the Internet. However, it would…
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…
Object detection is a branch of computer vision that focuses on identifying the presence and location of objects in images. It is used in a wide variety of applications, from surveillance systems, medical image analysis to autonomous driving. This technique…
In a previous blog article, we analyzed from a theoretical point of view which are the main libraries for data science and machine learning used by data scientists to treat data efficiently and extract its full potential. In this post,…