Machine Learning Project: Two models that predict the box office success of a movie released in the United States.
Garmin Fitness Dashboard: Creating visualizations using D3 to fill the gap in fitness apps.
Education-Home Price Analysis ETL Pipeline: ETL pipeline for sentiment analysis of sale price of homes and school scores in Virginia in 2018.
Weather Dashboard: Dashboard illustrates the relationship between weather and a location's proximity to the equator.
WeatherPy Challenge: How does your proximity to the equator effect the weather?
Big Data Challenge: ETL pipeline for Amazon reviews using pySpark with Zepl notebooks and loaded into an RDS instance.
Leaflet Challenge: Leaflet was used to visualize earthquakes based on their magnitude, latitude and longitude.
D3 Challenge: Created a scatter plot using D3 to illustrate the relationship between percent in poverty and percent lacking healthcare.
Plotly Challenge: A full stack app that is an interactive dashboard to visualize the belly button biodiversity dataset.
JavaScript Challenge: Created an HTML web page with an interactive table of UFO sightings
Web Design Challenge: Created a dashboard to visualize the results from the weatherPy Challenge.
Web Scraping Challenge: A flask app web scrapes, loads into a mongo database then serves up an html page about Mars.
Python Challenge: PyBank is a python script that analyzes a financial records data set, and PyPoll is a Python script that analyzes poll data.
Pyber Challenge: Matplotlib and Pandas were use to visualize a ride sharing company's data.
Employee Database SQL Challenge: Created a SQL database, ERD and sample quieries for employee information.
Excel Challenge: Excel was used to examine what makes Kickstart projects successful.
VBA Challenge: VBA was used to analyze stock market data.
Academy of Py: District-wise standardized test results were analyzed using Pandas.
Climate Analysis and Exploration: Flask API was created after exploring a climate database and created visualizations using Matplotlib.