In this project, I have gathered my listening history from my Spotify account using Spotify API. The data is then cleaned, preprocessed and transformed as required to avoid any aberrations that might later skew the results. Then performed data analysis on it to get a better understanding of my listening history, music taste, and choice of the artist.
Developed a proof of concept for Power BI embedding using the asp.net framework. This embedding implementation included row-level security, view-edit mode, interactivity features with the report. Used Power BI embedding API to implement it. Used Azure for hosting. Setup the SQL database for storing login credentials.
Handled incorrect, corrupted, incorrectly formatted, and duplicate in the web scraped cannabis dataset. Moreover, filled 60% of the empty data by extracting information from the existing data. Designed and created a Data warehouse for the same dataset by converting the flat file to star schema. Further, designed Power BI reports on the same dataset.
Analyzed the data with the help of standard descriptive analysis, Chaos theory, and pertinent visualizations. Designed an architecture for an LSTM model to forecast with a mean absolute error of 9.64. Published a paper titled - Air Quality Index - A Study to Assess the Air Quality, and another paper titled - Comparison of Time-Series Forecasting Models is submitted for publication.
In this project the risk factors associated with the cervical cancer in women is analysed. Then using the risk factors as independent variable for regression it is predicted whether they have cervical cancer or not.
