Jecoc907
USC Master of Business Analytics, Class of 2025
USC Marshall School of BusinessLos Angeles, California
Pinned Repositories
Airbnb-Amenities-Descriptions-Analysis
In this project, our team is interested in looking into the effect of “Above and Beyond” Descriptions of Amenities on Airbnb Ratings in Los Angeles.
ATP_players_age_vs_winning_analysis
The purpose of this project is to access the relationship between age and performance of professional tennis players
Causal-Relationship-Analysis-Twitch-viewership-vs-Active-Players-
In this project, our group is interested in whether there is causal relationship between a game’s Twitch viewership and its active player engagement. We are using the case of Tom Clancy’s Rainbow Six Siege as a primary example, and extending the analysis to Counter-Strike 2 and Rust.
Jecoc907
Jecoc907.github.io
Personal Website
LA-Airbnb-Market-Analysis-in-Covid-19-Period
The purpose of this project is to analyze and compare LA airbnb market before and during covid-19 period.
NBA-Player-Injuries-Analysis
The purpose of this project is to try to predict the occurrence of injuries based on player's in-game statistics.
NBA-Power-Partnership-Analysis
In this project, we want to learn why are certain basketball teams are successful. The 19-20 Lakers champion team was used as an example.
Options-Pricing-with-ML-models
Our goal in this project was to develop statistical and machine learning models to replicate the functionality of the traditional Black-Scholes option pricing formula, specifically for valuing European call options.
Streaming-Ecosystem-Analysis
In this project, we focused on a television studio and the decision-making process for producing our next TV show. We conducted a market analysis to understand the content offerings on mainstream platforms like Netflix, Hulu, and Amazon Prime Video, and explored potential market opportunities.
Jecoc907's Repositories
Jecoc907/Causal-Relationship-Analysis-Twitch-viewership-vs-Active-Players-
In this project, our group is interested in whether there is causal relationship between a game’s Twitch viewership and its active player engagement. We are using the case of Tom Clancy’s Rainbow Six Siege as a primary example, and extending the analysis to Counter-Strike 2 and Rust.
Jecoc907/NBA-Player-Injuries-Analysis
The purpose of this project is to try to predict the occurrence of injuries based on player's in-game statistics.
Jecoc907/NBA-Power-Partnership-Analysis
In this project, we want to learn why are certain basketball teams are successful. The 19-20 Lakers champion team was used as an example.
Jecoc907/Streaming-Ecosystem-Analysis
In this project, we focused on a television studio and the decision-making process for producing our next TV show. We conducted a market analysis to understand the content offerings on mainstream platforms like Netflix, Hulu, and Amazon Prime Video, and explored potential market opportunities.
Jecoc907/Airbnb-Amenities-Descriptions-Analysis
In this project, our team is interested in looking into the effect of “Above and Beyond” Descriptions of Amenities on Airbnb Ratings in Los Angeles.
Jecoc907/ATP_players_age_vs_winning_analysis
The purpose of this project is to access the relationship between age and performance of professional tennis players
Jecoc907/Jecoc907
Jecoc907/Jecoc907.github.io
Personal Website
Jecoc907/LA-Airbnb-Market-Analysis-in-Covid-19-Period
The purpose of this project is to analyze and compare LA airbnb market before and during covid-19 period.
Jecoc907/Options-Pricing-with-ML-models
Our goal in this project was to develop statistical and machine learning models to replicate the functionality of the traditional Black-Scholes option pricing formula, specifically for valuing European call options.
Jecoc907/Movie_Recommender_System
This project implements a movie and TV show recommender system using ReelGood data. Users should receive 3 movies and TV shows recommendations based on their input.
Jecoc907/NBA_players_efficiency_analysis_1
The purpose of this project is to study and predict NBA player's efficiency using Decision Tree Regressor model.
Jecoc907/NBA_players_efficiency_analysis_2
As a follow-up report to project 2, we enhanced our Decision Tree Regression Model by introducing ensemble algorithms, such as Bootstrap, Random Forrest, and XGboosting.
Jecoc907/NBA_Winning_Factors_Analysis
The purpose of this project is to analyze some winning factors for a NBA team and predict their win rate using multiple linear regression. Different cross-validation methods were used to evaluate the model's prediction ability.