Jolly I. Ogbolè (jolly-io)

jolly-io

Geek Repo

Location:San Francisco

Home Page:https://jolly-io.github.io/

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Jolly I. Ogbolè's repositories

Stock_Markets_Assymetric_Volatility_Spillover_Effects

I investigate the Asymmetric Volatility Spillover Effects within and across six major International stock markets. United States, Canada, France, Germany, Italy & Japan

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awesome-survival-analysis

Resources for Survival Analysis

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Azure_Reviews_A_Latent_Dirichlet_Allocation_Approach

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.

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Data_science_projects

data projects implemented in 2018 touching on a number of domains including real estate, healthcare, transportation etc.

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Exploratory_Data_Analysis_On_US_Domestic_Flights

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.

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jolly-io

Introduction

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Modeling_Customer_Churn_Prediction

In this project, the objective was to build a classification model to predict a customer’s likelihood to churn for ZQ, a telecommunications company.

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Random_Forest_and_Logistic_Regression

This is a classification model implementation using Random Forest and Logistic Regression in Python and Spark. Originally implemented via AWS EMR Clusters.

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Research_Writing_Samples

Select samples of my research work products

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Python-projects

Principles and Concepts Implementation

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Turo_Pricing_Prediction_Model

I develop a multilinear regression model for price prediction on car sharing platform, Turo.

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Yelp_Ratings_and_Restaurant_Reservations

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

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