Introduction: Regression algorithms predict continuous values from predictor variables. Predicting the price of a house based on its characteristics is a good example of regression analysis.In this article, I will implement univariate (one-variable) linear regression in python. Linear regression? What’s mean? Linear regression is an algorithm that will find a straight line that comes as […]
Introduction: Do you remember that data science is the combination of mathematics, statistics, and programming skills? We will see in this article which tools do we need to master data science. But I warn you that these tools are not the only ones and that you can use others at your convenience. 1. Python Python […]
Introduction: The data science process typically consists of six steps that are : Frame the problem, collect data, process data, explore data,modelize data, communicate the results. In this article we will face them one by one to finally be familiarize by the process of data science. 1. Frame the problem When it comes to perform a […]
Introduction: As the mathematician and data science entrepreneur Clive Humby said in 2006 ”Data is the oil” to say how important data is nowadays; data now feeds entire industries and has enormous value, so we will talk about two topics around data, namely data science (or data science) and data engineering (or data engineering). First […]
Introduction: With digitalization, we are living in an exciting time where data is flowing in from everywhere (mobile devices, computers, etc.). This information is collected, stored and processed in order to give it meaning. That is to say, this information is used to make marketing decisions, solve complex problems, react more quickly to change and […]
