This repository consists of Data Camp Projects of Data Visualisation, Machine Learning, Importing and Cleaning Data, Case Studies, Probability and Statistics and much more!!
I learned to use Jupyter Notebook.
Using a dataset comprised of songs of two music genres (Hip-Hop and Rock), I trained a classifier to distinguish between the two genres based only on track information derived from Echonest (now part of Spotify). I first made use of pandas and seaborn packages in Python for subsetting the data, aggregating information, and creating plots when exploring the data for obvious trends or factors you should be aware of when doing machine learning. Next,I used the scikit-learn package to predict whether you can correctly classify a song's genre based on features such as danceability, energy, acousticness, tempo, etc. I used common algorithms such as PCA, logistic regression, decision trees, and so forth.