Eric Jung Email & Phone Number

New York, New York, United States

New York, Ny, United States

New York, New York, United States

Brooklyn, New York, United States

Landing Zone ProjectInitiate a streamline process of transforming education data in non-standard formats into an interoperable format for the public education system to followWeb scrap and organize over 1000 public education data and research papers from multiple non-profit organizations' databases and catalogsAnalyze and present project partners and stakeholders' feedback to solve pain points for the developement of the Landing Zone APIConsult solutions with other project associates to make their projects' data pipeline more efficient

New York City Metropolitan Area

Completed Metis's 12-week accredited data science bootcamp focused on Python programming, machine learning, statistical modeling, data visualization, project design, and communication. Designed, implemented, and presented the following projects:1. What Are Those? - Shoe Image Classification Model-Built a classification model using TensorFlow and Keras to classify different models of shoes using convolution neural networks-Used transfer learning to train the model on a custom dataset of 1000 Nike shoe images- Achieved a model accuracy of 88% 2.Better Uber for Its Drivers: -Scrapped 10,000 Uber and Lyft Driver reviews using Beautiful Soup and Selenium-Analyzed sentiment values behind the scrapped reviews using VADER -Modeled topics using Non-Negative Matrix Factorization (NMF) to categorize the scrapped reviews in order to see which areas Uber could improve for its drivers 3. Coronary Heart Disease Predictor-Compared performances of multiple classification models ( random forest, logistic regression, KNN, SVM, and Naive Bayes) to predict whether patients have Coronary Heart Disease based on their data.-Best model has an accuracy of 75% with 96% Recall 4. NBA Player's Salaries Predictor-Modeled Player's data using Linear Regression, Lasso, and Ridge Regularization to estimate their salaries thru feature engineering-R^2 value of 0.745