Jolly I. Ogbolè's Projects
Resources for Survival Analysis
Background and Objective: My objective is to leverage the Latent Dirichlet Allocation (LDA), an NLP Topic Modeling technique to analyze the textual data aggregated from a particualr high impact reviews platform, capterra.com to uncover key trends and insights from the product users' perspective.
data projects implemented in 2018 touching on a number of domains including real estate, healthcare, transportation etc.
In this project, I undertook Exploratory Data Analysis (EDA) to investigate delays and reliability of airports.. Given the available dataset, I formulated and posed a number of insight eliciting questions and endeavored to answer these questions from the dataset leveraging the Pandas and Numpy libraries and relevant Visualization toolkits.
Introduction
In this project, the objective was to build a classification model to predict a customer’s likelihood to churn for ZQ, a telecommunications company.
Principles and Concepts Implementation
This is a classification model implementation using Random Forest and Logistic Regression in Python and Spark. Originally implemented via AWS EMR Clusters.
Select samples of my research work products
I investigate the Asymmetric Volatility Spillover Effects within and across six major International stock markets. United States, Canada, France, Germany, Italy & Japan
I develop a multilinear regression model for price prediction on car sharing platform, Turo.
In this project, I investigated the Association between Yelp.com ratings for restaurants and the availability of reservations. Result: I find a Negative correlation between high ratings and availability of reservations