itrustnumbers / music_genre_classification_by_model_ensembling_approach

This Project is my attempt at solving the music genre classification or MGR problem. I have used a model ensembling approach by bagging together the weighted prediction probabilities of three different classifiers. The algorithms used were XGBoost, CatBoost and Radnom Forest Classifer. My ensembled model was able to reach 97.8% Val. Accuracy

Greatings Fellow Earthling, I am Yash Chauhan

Welcome to my Github Profile, This is the home of my curated projects, experiments and some lossely packed ideas.

About Me:

• I am mainly interested in Artificial Intelligence, Machine Learning, Data Science and other related stuff. Some of my ML Projects:

  • Machine Learning Algorithms from Scratch | Current
  • Indian Coin Classification Using CNN | Finished

• Recently, I've also been quite intrigued by the idea of open source development, I am fairly new to the open source landscape and I've just started contributing. Currently I am contributing to this wonderful project here:

  • Basic Computer Games | Jeff Atwood

What I use on an average day(basically daily)