PROJECTS
MACHINE LEARNING & DATA ANALYSIS PROJECTS
Reasons Why Employees Quit | Human Resources Analytics
• Employee Turnover Prediction: The challenge was to determine the factors affecting employee turnover on a simulated company using various exploratory data analysis techniques and statistical testing. Implemented logistic regression, random forest, decision tree, and gradient boosting machine models for predictions.
• Deduced from extensive data mining that employee satisfaction, average monthly hours, and project count were leading factors in turnover.
Housing Price Prediction | Advanced Regression Techniques
• House Pricing Prediction: Imputed data according to the distribution of graphs. Applied a correlation matrix to test for high feature collinearity. Used Boruta/RandomForest package for feature importance and Gradient Boosting Machine (GBM) for predictive modeling.
• Platform - Kaggle - Rank - Leaderboard - Top 20% across the globe.
Titanic Survival Prediction | Machine Learning From Disaster
• Survival Prediction: Analyzed survival ratio of people who were in titanic. Applied feature engineering, data imputation, data exploration, R programming, and machine learning classification algorithm to predict which passengers survived the tragedy.
• Platform - Kaggle - Rank - Leaderboard - Top 10% across the globe.
My Blog
Read up.
Machine Learning | For the Fresh Bloods
August 16, 2017
Machines can predict the future, as long as the future doesn't look too different from the past.
Machine Learning | What's Inside the Box
August 16, 2017
Just like opening a box of chocolates, you shouldn't be afraid of knowing what is inside a #machinelearning algorithm. They're harmless, trust me.
Machine Learning | Accuracy Paradox
August 16, 2017
My third article about why using accuracy as a predictive measurement can be misleading! Is 95% accuracy on a model good?
Life of Data | Data Science is OSEMN
August 16, 2017
Believe it or not, you are no different than Data. Put yourself into data's shoes and you'll see why. Understanding the general concept on what the data science pipeline is like is crucial to manage a data science based project. This article will give you a high-level overview on how this "life cycle" works.
EDUCATION
EDUCATIONAL BACKGROUND
Springboard Data Science Career Track
July 2017 - January 2018
Data Science Curriculum - This online boot camp covers mastery of the data science process, from statistics and data wrangling, to advanced topics like machine learning and data storytelling
California State University - Long Beach
September 2012 - May 2017
Bachelor of Science in Computer Science
JOB EXPERIENCE
Affiliated Physicians IPA
Data Analytics Teacher Assistant
November 2017 - Present
Teacher Assistant for the Data Analytics and Visualization Bootcamp at University of Southern California
Claims Assistant
June 2015-August 2017
• Trained 3 new hires to use the MSO claim software
• Reviewed over 300 claims for quality and compliance.
• Provided excellent customer support.
LET'S BE FRIENDS
I don't bite.
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