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Data Ecosystem Research (Engineering, Science & Analytics) | Economics | Optimization Methods

I'm Jolly Ogbolè

  • 🛠️ Since my initial introduction to data science with Data 8 at UC Berkeley in the Spring of 2017, I have been utilizing Python SQL R & AWS to help organizations understand their data and impact business outcomes.
  • ⚡ I enjoy: reading, soccer, running(outdoors), plane spotting & a few more :)

Jolly I. Ogbolè's Projects

azure_reviews_a_latent_dirichlet_allocation_approach icon 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.

data_science_projects icon data_science_projects

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

exploratory_data_analysis_on_us_domestic_flights icon 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.

modeling_customer_churn_prediction icon 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.

random_forest_and_logistic_regression icon 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.

yelp_ratings_and_restaurant_reservations icon 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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