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  • 👋 Hi, I’m @ItsOyondi
  • 👀 I’m interested in Computer science, Information systems, Big Data, Data science and analytics, Information visualization, Machine learning, Artificiail Intelligence, and robotic process automation.
  • 🌱 I’m currently learning Data science and analytics at Grand Valley State University, MI. I am also learning RPA through online courses.
  • 💞️ I’m looking to collaborate on Data analysis, Programming, ML, AI and RPA projects and any other exciting Information technology project.
  • 📫 How to reach me: Email: [email protected]

itsoyondi's Projects

american-airlines-financial-performance icon american-airlines-financial-performance

This task involved an analysis of the American Airlines financial performance since 1995. The data was obtained from http://web.mit.edu/airlinedata/www/default.html.

bing-covid-19-data icon bing-covid-19-data

A repo for coronavirus related case count data from around the world. The repo will be regularly updated.

birds-classifier icon birds-classifier

I am currently working on this project. I am building a classifier model using Python CNN. I am using dataset obtained from https://www.kaggle.com/datasets/gpiosenka/100-bird-species

covid-19-data icon covid-19-data

Data on COVID-19 (coronavirus) cases, deaths, hospitalizations, tests • All countries • Updated daily by Our World in Data

covid-r-visualizations icon covid-r-visualizations

This project provides a visualization of Covid-19 spread on maps and other interactive graphs using plotly package and R-shiny. Guided by Dr. A.

dss-challenge---health-data icon dss-challenge---health-data

Data science competition: Task - How do the factors within a person’s control and outside a person’s control affect their wellbeing?

e-commerce_tv_sales icon e-commerce_tv_sales

The data was obtained from https://www.kaggle.com/datasets/devsubhash/television-brands-ecommerce-dataset.

holiday-events icon holiday-events

This simple project was used to examine the distribution of events per locale - local, regional or national in holidays across various countries. The project employs machine learning (LR) to predict whether the holiday events were transferred or not. The findings indicated that majority of the events were not transferred and regardless of the locale, there were 7% chances of an event being transferred.

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