Collaborated to create a Machine Learning model trained and tested with a Random Forest model to predict primary emotion based on input audio file. Data cleaned and trained in a Jupyter Notebook using Pandas and Librosa. Results visualized using Pandas, Tableau and JavaScript functions with bootstrap in a dynamic HTML website.
Full Stack App: Worked collaboratively to create an interactive website displaying information on popular cocktail recipes. Gathered data from csv files as well as web scraped data from google articles. Explored and cleaned data using Pandas in a Jupyter Notebook. Designed a database in PostgreSQL to store data. Created a website using Bootstrap HTML/CSS and interactive visualizations using multiple Javascript libraries including Plotly, Geomapping with Leaflet.js.
Created a story in Tableau to visualize CitiBike data from 2019 before the pandemic and 2020- after the pandemic to see how it has affected ridership. Cleaned data in a Jupyter Notebook. Created multiple visualizations and dashboards to illustrate the changes or lack of change to ridership and station popularity. Offered suggestions to CitiBike based on conclusions.
Designed a responsive website using Bootstrap HTML and CSS to display climate data visualizations made in Python using Pandas, Matplotlib, API Request calls, and Google Maps API in a Jupyter Notebook.
