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austin_project

This repository contains my final project for UT Austin's Data Analytics Bootcamp. My teammates and I explored a Wine Reviews dataset and built an interactive Tableau dashboard to recommend wines for a novice based on price, rating, variety, and country. We also built a machine learning model to train it to rate wine like an experienced sommelier.

belly_button_biodiversity

JavaScript and Plotly.js to explore data on the biodiversity of belly buttons.

big_data_m16

bikesharing

Tableau used to create and present a business proposal for a bike-sharing company.

credit_risk_analysis

Predicted credit risk with the supervised machine learning models through Python.

cryptocurrencies

Unsupervised machine learning techniques to analyze cryptocurrency data.

election_analysis

Automated the vote-counting process for a local election with Python and Visual Studio Code.

kickstarter-analysis

Performing analysis on Kickstarter data to uncover trends using Excel.

mapping_earthquakes

JavaScript's Leaflet library paired with the Mapbox API to create visualizations of earthquake data retrieved from the U.S. Geological Survey website.

mechacar_statistical_analysis

Statistics and hypothesis testing to analyze a series of datasets from the automotive industry.

mission-to-mars

Web application to scrape websites for data about the Mission to Mars. Created an HTML page using Flask.

module1

module_11_ufos

JavaScript, HTML, and CSS to create a custom webpage that showcases different UFO sightings around the world.

movies-etl

Performed ETL on several movie datasets to predict popular films for a streaming service.

pewlett-hackard-analysis

Created entity relationship diagrams (ERDs), performed data modeling, and completed analysis on an employee database using PostgresSQL via pgAdmin4.

plotly_deployment

portfolio

pyber_analysis

Analyzed and created visualizations using ride-sharing data through Python, Pandas, and Matplotlib.

school_district_analysis

Used Python and Pandas to analyze school district data to reveal trends in school performance.

stock-analysis

Explored green energy stock performance by analyzing financial data using Microsoft VBA.

surfs_up

Python, SQLAlchemy, and Flask to analyze and visualize climate data.

ufos

JavaScript, HTML, and CSS to create webpage about UFO sightings around the world.

world_weather_analysis

Using latitude and weather for cities around the world created relationships using Python, Pandas, and APIs.