A data-driven organization will use data as critical evidence to help inform and influence strategy. There will be an evidence-based culture where findings found from data will be factored into decisions.
Classification problems are the most frequent use cases encountered in the real world. Unlike regression problems, where an actual numerical value is predicted, classification problems attempt to associate an example with a category.
Regression is one of the key methods regularly used in data science to model relationships between variables, where the variable to be estimated is a continuous number.
Machine Learning is gaining more and more strength nowadays. In this publication we explain in a friendly way what it is and what are the different types of Machine Learning that exist.
When it comes to inclusion, Data Science is a clear example of it. The applications of data science are many and are not limited to specific areas.
Technological growth is exponential, as is the data generated. However, it is estimated that less than 20% of the data created is analyzed. In this article we will talk about the raw material of our solutions, the data.
