Machine learning techniques

I-LingYeh

PITTSBURGH, PA

412-***-**** ************@*****.*** iling82816.github.io/ILing_website/ ILing82816 ILingYeh Skills

Language Fluent in English, Native in Mandarin

Programming Language Python, R, MATLAB, JAVA, Scala, HTML, CSS, JavaScript Machine Learning Spark, Hadoop, MySQL, Python (eg. scikit-learn, numpy, pandas, marplotlib), R (caret, dplyr, tidyr, ggplot2) Data Science Technologies Data science pipeline (cleaning, wrangling, visualization, modeling, interpretation), Statistics, Time series, APIs, Git Work Experience

Research Assistant, Institute of Economics, Academia Sinica Taiwan,Jul. 2017 – Feb.2019

• Utilized matlab to compute regression model to discover the optimal labor wage.

• Presented results to professor and wrote research summary for further publish. Teaching Assistant of Macroeconomics, National Sun Yat-sen University Taiwan,Feb. 2017 - Jun. 2017

• Collaborated with instructor to lead recitations, grade coursework, and answer 100+ students’ questions. Achievement

ANZ Virtual Experience Program Participant Aug. 2020

• Wrangled trading data using python to remodel and visualize the dataset to track location of transaction.

• Utilized python to implement supervisedmachine learning techniques for identifying the annual salary for each customer. Education and Honors

M.S. Information Science, University of Pittsburgh, PA Apr. 2021

• Cumulative GPA: 3.8/4.0

• Relevant coursework: Machine Learning, Intro of Neural Networks, Data Mining, Cloud Computing M.A. Economics (GPA: 3.91), National Sun Yat-sen University, Taiwan Jun. 2017

• Cumulative GPA: 3.9/4.0

• Relevant coursework: Linear algebra, Logistic Regression, Time Series Analysis

• Awarded with the President’s Scholarship for Exceptional Performance in Academic B.A. Economics (GPA: 3.59), Tunghai University, Taiwan Jun. 2015

• Cumulative GPA: 3.6/4.0

• Relevant coursework: probability distribution, Hypothesis Testing, p-value Projects

Crude Oil WTI Price Estimator

• Utilized python to implement Long Short-term Memory algorithm for predicting oil WTI prices.

• Collected over 25 years economic indicators and crude oil prices.

• Predicted correctly the crude oil stock price are whining the range of $48-55 by the end of 2020. Prediction of Complex System Performance

• Utilized R to implement supervisedmachinelearningtechniquesforcomparingtwosystemprocessesthatinfluencemostlythecom- ponent probability of fail.

• Optimized the system by using Binary classification model(Logistic regression, Neural network, Random forest, Gradient boosted tree).

Prediction of Length of Stay Post-surgery

• Utilized python to implement supervised machine learning techniques for identifying the important variable that influence mostly the risk of surgery.

• Used a real, anonymized dataset provided by UPMC regarding surgical procedures between June 2017 and June 2018.

• Optimized Logistic Regressor, Random Forest, XGBoost, and LightGBM using Hyperopt to reach the best model. Classification of Twitter Sentiment

• Utilized python to implement unsupervisedmachinelearningtechniquesforobservingthepopulationofAmerican2020presidential candidates. lose up to 20% positive discussions in 2020 than in 2016.

• Used Twitter APIs to scrape about 10000 tweets.

• Predicted one of candidates lose up to 20% positive discussions in 2020 than in 2016. JANUARY 26, 2021 I-LING YEH · RESUME 1

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