Description
The session will provide students with an overview of the quantitative methods implanted in quantitative research designs involving data analytics, machine learning and discrete event simulation. Students will learn about concepts of preprocessing techniques to prepare data for successful analytic purposes.Topics:
-Data cleaning and data preprocessing:
data cleaning (i.e., missing values, outliers, and errors); data integration; data transformation; data reduction; data discretization
-Performance matrix: Confusion matrix for a single class and multiclass classification;
- Python implementation and evaluation