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annotations-infrastructure

django-sample-application

etl-example

fairtest

fraud-detection-in-python

Classifying and predicting fraudulent transactions using BankSim data

gouldju1

honr39900-foundations-of-geospatial-analytics

Maps are everywhere around us: in our cars, on our phones, and driving public health initiatives. Geospatial skills and knowledge are increasingly sought after in industry, and will continue to prove vital to Data Science. You will learn how to create maps and analyze spatial data using Python and SQL, how spatial data are applied in a variety of domains, and have hands-on experiences with real data. Together, we will answer questions such as: (1) what are maps, (2) how can we create maps from data, (3) and how do we quantify and analyze maps. Applied geospatial projects will include: autonomous vehicles, public health, supply chain, and more.

michiganstatefootballtriviagame

Michigan State Football Trivia Game for Amazon Alexa

microservices-demo

motor-trend-car-test-data-k-means-shiny-app

mtcars Shiny app using K-Means

presidentfacts

r2sql

:hot_pepper: R²SQL: "Dynamic Hybrid Relation Network for Cross-Domain Context-Dependent Semantic Parsing." (AAAI 2021)

russian-troll-tweets-network-analytics-in-r

srv-topic-sentiment-analysis-in-r

Topic and sentiment analyses of top 5 SRV songs on Spotify

titanic-project-stats-883

MSU ITM 883 Project