Long quiz_FPA

is crucial for predictive analytics because it helps improve the accuracy and reliability of the models.

for predictive analytics is the process of preparing raw data for use in predictive models.

Data do not always come in a form that is immediately suitable for analysis. We often have to transform the variables before carrying out the analysis. In some instances it can help us better examine a distribution.

preserves linear relationships between variables. Therefore, the correlation between x and y would be unchanged after a linear transformation.

changes (increases or decreases) linear relationships between variables and, thus, changes the correlation between variables.

is the process of extracting good, reliable data from these sources.

This involves converting data from one structure (or no structure) to another so you can integrate it with a data warehouse or with different applications.

is a subset of artificial intelligence that allows systems to learn and improve from experience without being explicitly programmed.

It's about building algorithms that can identify patterns in data and make decisions or predictions based on those patterns.

Algorithms learn from labeled data.