Hong Gao

I am passionate about data science. I have in-depth understanding of a variety of Machine Learning algorithms including Support Vector Machines (SVM), Naive Bayes, k-Nearest Neighbors (KNN), and Random Forest. I have developed and validated predictive models to guide business decisions in banking industry. I have used statistical tools in medical research for more than 10 years. I analyzed next generation sequencing (NGS) data to extract hidden insights. Each NGS data set contains 20 to 400 million sequences. I published one paper in unsupervised learning based on microarray data. My experience demonstrates my ability in handling big data and applying statistical analysis to reach significant and meaningful conclusions. I finished two courses with Code Louisville in 2016. During this continuing education, I built two websites and acquired hands-on experience with computer programming, relational and non-relational databases, and Linux operating systems. Specialties: SAS, R, Python, SQL, Statistics, Predictive Analytics, NGS data analysis