Visualizing Machine Learning Baseball in Python


Details
Can you predict a Major League Baseball (MLB) team’s playoff success from their regular season series win percentage? On Tuesday June 6th at 6 pm join MacKenzye Leroy’s Pythonic journey to find the answer. His path traces through the processes of scraping the results of MLB games going back to 1900, data cleaning and analysis. He will show the importance that interactive plots play in understanding the answer and how these visualizations can be deployed as a dashboard on Amazon Web Services (AWS). Check out his final product at http://52.14.213.53:8501/
On this journey MacKenzye’s talk will cover the following tools in Python:
-Beautifulsoup for data acquisition
-Pandas/numpy for data cleaning
-Plotly for interactive plots
-Streamlit for turning plots into a full-fledged dashboard
-AWS for dashboard deployment
He will also touch on how the skills developed in his journey intersect with his work at S&P Global Market Intelligence.
MacKenzye Leroy is a Data Scientist at S&P Global and a recent graduate of UVA’s M.S. in Data Science Program. He is fascinated with finding interesting answers to complicated problems. When he is not wrangling data the former collegiate Cross Country and Track athlete has traded in long miles on the road for quality time in the mountains. If indoors he is probably cheering on his beloved New York Mets and New York Giants.
Want to practice your presentation skills? Before MacKenzye’s talk we have space for a couple lightning talks (up to 7 minutes). This is a great opportunity to develop communication skills for interviews, work, and have something to add on your resume. If interested please message Paul Otto on Meetup.
When: Tuesday June 6th from 6:00 pm - 7:30 pm
Where: S&P Global, 212 7th St NE, Charlottesville, VA 22902
Directions: See Meetup Directions

Visualizing Machine Learning Baseball in Python