Discover @ebunoluwazaynab Open Source projects

Zaynab Awofeso (@ebunoluwazaynab)

ebunoluwazaynab

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Registered over 4 years ago
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71.4 %

Python
14.3 %

TSQL 14.3 %
Location 🇳🇬 Nigeria
Country Total Rank 2,003
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Jupyter Notebook
145

Python
673

AdventureWorks-DB-EDA-with-SQL-and-PowerBI-

Microsoft AdventureWorks Database analysis using MS SQL Server and visualization with PowerBI.

Merge-Sort-Algorithm

This is a Python implementation of the merge sort algorithm. Merge sort is a divide-and-conquer sorting algorithm that recursively breaks down an array into two halves, sorts each half independently, and then merges the sorted halves back together to produce a final sorted array.

Real-Fake-Job-Postings-EDA

She Code Africa Mentoring Program Technical Assessment

Jupyter Notebook

Spaceship-Titanic

Kaggle recently launched a fun competition called Spaceship Titanic. It is designed to be an update of the popular Titanic competition which helps people new to data science learn the basics of machine learning, get acquainted with Kaggle's platform, and meet others in the community. This repository is a beginner friendly analysis of the Spaceship Titanic Kaggle Competition. It covers steps to obtain any meaningful insights from the data, and to predict the "ground truth" for the test set with an accuracy of ~80 percent using RandomForestClassifier.

Jupyter Notebook

COVID-19-DATA-ANALYSIS-PROJECT

This project employs data science & analytics skills to collect data, explore the data, perform analysis, create visualizations, and generate insights on the trend of the virus in Nigeria and the impact on the Economy.

Titanic---Machine-Learning-from-Disaster

Use machine learning to create a model that predicts which passengers survived the Titanic shipwreck

Jupyter Notebook

Loan-Prediction

Jupyter Notebook

Employee-Burn-Out-Rate-

Understanding what will be the Burn Rate for the employee working in an organization based on the current pandemic situation where work from home is a boon and a bane. How are employees' Burn Rate affected based on various conditions provided?

Jupyter Notebook