Miami, Florida, United States
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Experience & Education

  • Alteryx

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Courses

  • Analysis in R^n I-III

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  • Categorical Data Analysis

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  • Econometrics (Honors)

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  • Financial Accounting (Booth School of Business)

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  • Intermediate Micro I-II

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  • Intro to Computer Science I-II

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  • Investments (Booth School of Business)

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  • Numerical Linear Algebra

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  • Optimization

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  • Pattern Recognition

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  • Time Series Econometrics

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Projects

  • Digit Recognition

    Implemented the following classifiers to recognize hand-written digits based on their pixel representations in the MNIST data set:
    Linear Discriminant Analysis: 14% Classification Error
    Bernoulli Mixture Model with Dirichlet and Beta priors: 11% Classification Error
    Support Vector Machine: 10% Classification Error
    Logistic Regression: 13% Classification Error

    This was implemented in R.

  • Labor Supply of NYC Taxi Drivers

    Estimated the labor supply behavior of NYC taxi cab drivers with three other students of my Honors Econometrics class.

    Built a probit model to estimate the probability that a driver would end his/her shift after a given trip as a function of the income earned and the hours worked thus far in the shift.

    Given our dataset, the model showed that taxi drivers care more about the hours they have worked than the money they have earned when they are deciding whether or not to stop…

    Estimated the labor supply behavior of NYC taxi cab drivers with three other students of my Honors Econometrics class.

    Built a probit model to estimate the probability that a driver would end his/her shift after a given trip as a function of the income earned and the hours worked thus far in the shift.

    Given our dataset, the model showed that taxi drivers care more about the hours they have worked than the money they have earned when they are deciding whether or not to stop working.

    All of the data cleaning and analysis was done in R.

  • The Power of Jeopardy's Daily Double

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    I am an avid fan of Jeopardy and have debated whether or not I should apply to be a contestant. One of the factors holding me back was that I was worried the Daily Double had an outsized impact on determining the winner. After all, what would be the point of preparing for years only to lose because of chance?

    Rather than ponder about this philosophically, I decided to answer this question by scraping 17 years worth of Jeopardy data. I found that although players who answer the Daily…

    I am an avid fan of Jeopardy and have debated whether or not I should apply to be a contestant. One of the factors holding me back was that I was worried the Daily Double had an outsized impact on determining the winner. After all, what would be the point of preparing for years only to lose because of chance?

    Rather than ponder about this philosophically, I decided to answer this question by scraping 17 years worth of Jeopardy data. I found that although players who answer the Daily Double correctly are twice more likely to win than those who do not, this effect vanishes when you control for player quality. In fact, taking player quality into account, contestants who answer one Daily Double correctly only have about a 2-3% higher chance of winning than those who don't.

    The key takeaway is that aspiring Jeopardy contestants, myself included, should not need to worry about landing on the Daily Double. The data shows that better players tend to win on average, even if they don't land on the Daily Double and the only way to get better is by studying a lot. That doesn't bother me!

    PS: You can read my full analysis here - https://medium.com/s/story/does-the-daily-double-determine-who-wins-on-jeopardy-465378725826

    Here is my python code for scraping the Jeopardy Data: https://github.com/freddyalfonsoboulton/Jeopardy

    Here is the code I used to analyze the impact of the Daily Double: https://github.com/freddyalfonsoboulton/daily_double

    See project

Languages

  • English

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  • Spanish

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