Alexander
Levin-Koopman
As a lecturer in Applied Data Science at the University of Michigan School of Information, I'm passionate about solving problems through insights extracted from complex data sets. With a Master's degree in Applied Data Science (4.0 GPA) from the University of Michigan and a Bachelor's degree in Mathematics from the University of Colorado at Boulder, I've developed a strong foundation in statistical analysis, machine learning, and data visualization.
My academic background has equipped me with a unique ability to approach problems from multiple angles, think creatively, and communicate complex ideas effectively. While my experience is rooted in academia, I'm eager to apply my skills in a real-world setting and drive business outcomes through data-driven decision making.
I thrive on solving intricate problems and uncovering hidden patterns in data. My goal is to leverage my expertise to inform strategic decisions, optimize processes, and create value for organizations. If you're looking for a driven and analytical problem-solver who is passionate about data science, let's connect!
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SQLite Database of the Yelp Dataset
Project description: This project focussed primarily on implementing and populating the database with the yelp dataset. It contains users, reviews, business, tips, checkins, and photos. These tables and their relationships were examined, and a networkx graph was build based on the user friend groups.
YelpDataBase Class | Database Inspection
Figure 1: Entity Relationship Diagram
Figure 2: Friend Graph Degree Histogram
This plot shows up to degree 40. However the maximum degree is 6869 in the graph. This was done for the sake of visualizing the degree distribution.
