Using Spotify API
to extract Song details from Playlist
Extracted song details from a playlist using Python and the Spotify API, using Pandas for data processing.
Telecommunications
Customer Churn Prediction
Developed a machine learning model to predict customer churn using Pandas, Seaborn, and Scikit-learn. Conducted exploratory data analysis, feature engineering, and trained models like Logistic Regression and Random Forest. Evaluated model performance to provide insights for reducing customer churn.
Using Spotify API
Employee Exam Analysis
using SQL
Exploratory Data Analysis and Tailored Data Analysis done using SQL on Employee Promotion Dataset for Emerald Mobile Telecommunication Company.
Bank Customer Churn Analysis
using Pandas, Seaborn & Scikit-Learn
Performed EDA and built machine learning models to identify key drivers of customer churn. Achieved 87% model accuracy and recommended strategies to improve customer retention.
Customer Churn Analysis
using PowerBI
This dashboard was built for the Bank Churn Analysis done, it indicated the profile of a churned and a non-churned customer and highlighted key insights that contribute to churning.
Data Cleaning on
Fifa 21 Dataset
The project was done as a challenge conducted by @DataChallengeSp and @PromiseNonso_. This project was done using Python (pandas). The jupyter notebook and the cleaned up dataset is saved in the repository.
Housing Data Analysis
with SQL
This project using SQL involves analyzing housing data. The dataset includes information on various features such as ocean proximity, median house value, households, population, total bedrooms, total rooms, housing median age, latitude, and longitude. The purpose of this project is to explore the relationships and patterns within the dataset to gain insights.
Covid-19 Layoffs
Vizualization
This project was conducted using PowerBI and it visualizes industries, companies, countries and continents that had the most layoffs during the Covid-19 Pandemic.