Shan Kwan Cho has experience in software development, IT administration, and programming tutoring. They have also completed several machine learning projects involving Twitter sentiment analysis, merchant category recommendation, loan eligibility prediction, and Google stock price prediction. They are seeking an internship or career to further develop their skills in computer science, machine learning, deep learning, and artificial intelligence.

1. SOFTWARE DEVELOPER: INTERN
Zapptitude, Inc. | Mountain View, CA | May 2018 – August 2018
• Developed a native Android application for first grade math per Common Core Standards using Zapptitude’s
assessment analytics SDK to track students’ application usage.
• Sketched product design using Trello, Invision, and Model-View-Presenter. Built and implemented the application
using Java and implemented in Android Studio.
IT ADMINISTRATOR: INTERN
Zuckerberg San Francisco General Hospital and Trauma Center, Department of Public Health |
San Francisco, CA | July 2017 – April 2018
• Supported services utilizing IP data networks including servers, workstations, healthcare administrative software
applications (AeroScout RTLS), VoIP phones, Audio Visual Services, building security systems, patient telemetry,
and telehealth applications.
• Worked with Convergent Technologies partners to provide IT service transition, unified communications, clinical
communication systems, telehealth services, Stryker and Cisco Spark.
PROGRAMMING TUTOR
City College of San Francisco | San Francisco, CA | August 2015 – May 2018
• Tutored students in computer-related subjects (Java and Linux OS).
• Assisted the faculty monitors and the Technical Support Staff with everyday lab operations.
SHAN KWAN CHO
TWITTER SENTIMENT ANALYSIS
• Built, trained, and tested multiple classification models to detect whether certain tweets were hate speech or not.
• Initially developed a predictive model on raw data without pre-processing, achieved bad average prediction
accuracy of only 61%.
• Addressed the issue of poor model performance by conducting data pre-processing involving using the bag of
words technique to generate more precise features.
• Achieved 72 % of accuracy by developing Linear Support Vector Machine classifier along with own developed
features.
Utilized: Numpy, Pandas, Seaborne, Scikit-Learn, Random Forest, Linear Support Vector Machine
ELO MERCHANT CATEGORY RECOMMENDATION
• Participated in a Kaggle Competition that focused on helping ELO, a Brazilian payments company, developed
algorithms to offer personalized promotions and discounts to consumers and helped business partners to drive
economic growth.
• Sampled and merged business data from different sources, performed pre-processing on the aggregated data,
and conducted feature engineering to remove outliers, performed categorical embedding, and extracted new
features.
• Built LightGBM and CatBoost models, applied stratifiedKFold for model optimization, and generated predictions
of customer loyalty metric, landing in the top 16% of the competition.
Utilized: Numpy, Pandas, TimeSeries, Scikit-Learn, Lightgbm, Catboost
LOAN ELIGIBILITY PREDICTION
• Participated in an Analytics Vidhya Competition that involved in developing a real-time classification system to
determine whether or not customers are eligible for home loans
• Performed data pre-processing and feature engineering in order to determine which features are most relevant to
predicting home loan eligibility.
• Built a XGBoost classification model, used the grid search algorithm for model optimization, and evaluated model
performance using a Confusion matrix,
Utilized: Logistic Regression, Decision Tree, Random Forest, XGboost, NumPy, Panda, Matplotlib
GOOGLE OPENING STOCK PRICE
• Predicted Google opening stock price based on last 5 years’ data of Google Stock Price
• Used RNN(LSTM) alongside Keras framework based on data structure with 60 timesteps with 1 output, or based on
the trends during the 60 Time Steps; obtained loss of 0.023
Utilized: Deep Learning, RNN, LSTM, Machine Learning, Keras
CONTACT EXPERIENCES
MACHINE LEARNING/ DEEP LEARNING
Academy Bootcamp | mlacademy.io
December 2018
DEEP LEARNING SPEACIALIZATION
Deeplearning.ai | coursera.org
February 2019
RECOGNITION OF COMPLETION
Google Cloud |Cloud On Board
May 2018
415-695-4576
shankwancho@gmail.com
San Francisco, CA
linkedin.com/in/shancho
SKILLS
Programming Languages:
Python, Java, C, C++
HTML, CSS, JavaScript, PHP,
Bootstrap, MySQL
Technologies:
Git, GitHub, Google Cloud
Platform, Android Studio, Trello,
Cisco Spark
AI/ML: Tensorflow, PyTorch,
Keras, Time Series, Sci-kit Learn,
OpenCV, Neural Networks, ANN
PROJECTS
EDUCATION
BACHELORS |
COMPUTER SCIENCE |
MINOR in MATHEMATICS
San Francisco State University |
San Francisco, CA
2017 – May 2019
ASSOCIATES | MATHEMATICS &
COMPUTER SCIENCE
City College of San Francisco |
San Francisco, CA
2014 – 2017
CERTIFICATIONS
Objective: Seeking an internship or career opportunity that will allow me to utilize my problem-solving skills and attention to detail to further
develop my abilities in the field of computer science; specialization in machine learning, deep learning, and artificial intelligence.
github.com/ShanKwanCho
shancho.me