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…
Introduction 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…
Introduction 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…
Introduction 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…
Introduction Data science is an interdisciplinary area that deals with extracting knowledge and useful information from data. Given the large amount of data generated by companies, it is important for data scientists to have tools that facilitate the manipulation, analysis…
Introduction Regression is a statistical methodology that describes the relationships between a continuous explained variable and a set of explanatory variables. In other words, regression models are able to predict the value of a dependent variable y with respect to…
Introduction In the world of data science and analysis, time series are a key element, as they represent a very natural source of information: values of a magnitude at different points in time. This is why understanding their properties and…
Introduction I love writing posts for Damavis’s blog because it allows me to share my passion for Big Data and consulting. It’s also a great way to connect with other consultants and potential clients. I enjoy being able to provide…
Introduction Logistic regression is a statistical methodology that allows modeling the relationships between a binary categorical variable and a set of explanatory variables. Specifically, it models the probability that an observation belongs to one of the categories of that binary…