Software Tools for Demographic Sequence Analysis

Student: Islam Robiul

Educational Programme: System and Software Engineering (Master)

Year of Graduation: 2020

In this thesis, we present a comprehensive system for Demographic sequence data. These data-sets provided some demographic and socioeconomic events of the deference phase of life. Different visualization techniques are integrated into the system to find more detailed information and visualize. We also develop the interpreting machine learning model focusing on the black box technique to understand the most critical and influence events for a particular sequence.

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