  The aim of this study is to teach an algorithm how to recognize different
types of music. Users will submit songs for analysis. Since the algorithm
hasn't heard these songs before, it needs to figure out what makes each song
unique. It does this by breaking down the songs into different parts and
studying things like rhythm, melody, and tone via supervised learning because
the program learns from examples that are already labelled. One important thing
to consider when classifying music is its genre, which can be quite complex. To
ensure accuracy, we use five different algorithms, each working independently,
to analyze the songs. This helps us get a more complete understanding of each
song's characteristics. Therefore, our goal is to correctly identify the genre
of each submitted song. Once the analysis is done, the results are presented
using a graphing tool, making it easy for users to understand and provide
feedback.
