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Name: Zak Krumlinde
Type: User
Bio: A current high school teacher with a passion for all things data. An aspiring data scientist with an MS in Data Science from Lewis University.
Location: Joliet, IL
Name: Zak Krumlinde
Type: User
Bio: A current high school teacher with a passion for all things data. An aspiring data scientist with an MS in Data Science from Lewis University.
Location: Joliet, IL
I have created a dataframe to analyze Vegas' predictions on NFL games in 2017. It involves both teams, the spread (from Westgate), and if the projected team (it does not matter if they covered the spread, just if they won)
project2-zkrumlinde created by GitHub Classroom
This was a Kaggle competition. It involves predicting housing prices given the features and location of the house. There was a lot of time spent on data preprocessing, dealing with missing values and transforming the dependent variable. A lasso regression model was created to make the final predictions on the testing set.
The goal of this project was to learn how to web-scrape. Once all the data was scraped, an exploratory data analysis was done to determine that players that rank best in Greens in Regulation and Putting perform well at the Masters. For a complete write up, check out my Medium blog post, 'How to Win the Masters'
This model attempts to predict the number of bike checkouts at Divvy stations during each hour using a Random Forest.
Using machine learning techniques (Logistic Regression, Support Vector Machine and Decision Tree), I attempted to predict if a student passed their class based on the given quantitative and categorical data.
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