• Created a model to predict companies likely to churn from PowerCo - an energy company.
• Classified the factors that affected the company churn using Random Forest Classifier and feature importance.
• Achieved 90% accuracy in the model, using Keras in TensorFlow.
• ********-Open-Access-Data-Science-Advanced-Analytics-Virtual-Experience-Program
• Conducted analysis on bank’s dataset to predict fraudulent transactions.
• Achieved 92% accuracy in the model, using Logistic Regression to predict the fraudulent transactions.
• Conducted analysis on customers transaction dataset to predict annual salary.
• Utilized Random Forest Regression, Linear Regression and Decision Tree Regression for the predictive modelling.
• ********-Data-Science-and-Analytics-Virtual-Internship--Forage
• Queried databases stored in a Big Data platform.
• Produced KPI’s allowing the business to make informed decisions and target high valued customers.
• Reviewed content of internet search results.
• Rated keywords and search term pairs.