Portfolio

COURSE Projects

covid-19 (Business intelligence)

eMERGENCY ROOM (SIMULATION)

personal loan (machine learning)

WISCONSIN BREAST CANCER (multivariate analysis)

TOYS-R-4-U (OPTIMIZATION)

PERSONAL Projects

MEYER VAHLE COLLECTIVE (logo/WEB DESIGN)

Atlas tables (logo design)

le bleu (menu design)

For this business problem, I used discrete event simulation to model a complex querying system used in an emergency room. Utilizing R, I simulated the specific measure of performance that includes the average number of patients waiting, the average wait time of patients, the average total time or flow time, the average utilization of resources to determine the most efficient method to handle incoming patients.

A COVID-19 data set was selected for a business intelligence project/report where my team and I demonstrated data cleaning, merging, analysis, and visualization. Tableau and Python was utilized to visualize the data. Additionally, the details of the work performed and the quality of the data were reported.

For this assignment, I calculated the probability of a person accepting or rejecting a personal loan based on attributes from the dataset provided and visualized the data using decision tree models. Different machine learning techniques were used including boosting, bagging, and random forest to determine the highest accuracy rate in its performance.

A Wisconsin Breast Cancer data set was selected by my team and I where we utilized R to performed various multivariate analysis methods. Insight was created through various techniques including dimensional reduction, cluster analysis, and confirmatory factor analysis.

In this business problem, a toy company wants to determine how many units of each toy should be produced to maximize profit. I utilized Python to formulate a Mixed Integer Programming (MIP) model that calculates the optimal number of units to produce and maximum profit based on the criteria given.

Last Updated: 7/22/21 6:57 PM CST