esikäsitlemist
Esikäsitlemist, often translated as "pre-treatment" or "pre-processing," refers to the preparatory steps taken before a main process or analysis. This concept is broadly applicable across various fields, including data science, manufacturing, and scientific research. In data science, esikäsitlemist involves cleaning, transforming, and organizing raw data to make it suitable for machine learning algorithms or statistical analysis. This can include handling missing values, normalizing data, encoding categorical variables, and removing outliers. The goal is to improve data quality and the accuracy of subsequent models.
In manufacturing, esikäsitlemist relates to preparing raw materials or components before they undergo further processing. This