BUDDY MASTER: SMART STUDY PRIORITY ANALYZER USING MACHINE LEARNING

Text from a course outline is analyzed
in a way called as Study Priority Analyzer. The
topics is determined by analyzing word patterns
that are recognized by specialist. One of the
approaches is machine learning methods rather
than sorting. Natural language processing is a
part of analyzing. Decisions on priorities carries
the frequency and context analysis. A statistical
model called logistic regression is used.
Students get an idea of what priorities first and
the guess prediction carried out with high
accuracy. Prioritization is an Interpretation of
structured data. The software accepts different
file formats; however, its strongest point is
helping students focus on important topics.
While helping students organize study material,
it identifies priorities so time is used efficiently.