Awesome
<h1 align='center'>CCE: COVID-19 Case Estimator</h1> <img align='center' src = "https://region8today.ieeer8.org/wp-content/uploads/sites/4/2020/05/ieee-hac-covid19.png"/> <p align = 'center'>We aim to use what we learnt in the Optimization Techniques Course at Alexandria University, Faculty of Engineering Spring 2020 offering to understand the <b>causes promoting COVID-19 spread</b> and <b>create an estimator</b> for the COVID-19 number of daily cases and total cases for some countries.</p> <p align = 'center'> <a href="https://drive.google.com/file/d/1JOawVy8QQkgckJzqVc4zzFTrlGTrzxZ_/view?usp=sharing">Problem Statment</a> <b> . </b> <a href="#intro">Overview</a> <b> . </b> <a href="#work">Work Organization</a> <b> . </b> <a href="#team">Contributors/Acknowledgments</a> </p><a name="intro"></a> Overview
COVID-19 is a great danger to the whole world and that's something everyone probably already knows as long as they weren't living under the cave the past couple of months for some reason.
Without data we can not understand the pandemic. Only based on good data can we know how the disease is spreading, what impact the pandemic has on the lives of people around the world, and whether the counter measures countries are taking are successful or not. But even the best available data on the coronavirus pandemic is far from perfect.
That's where we come along, Software Engineers meet Data Scientests and professionals and try using the available data to create models that can predict, understand and model the future of the world under the hood of COVID-19. We wish with this work we add upon the acheivements of many to counter this pandemic and seek to understand more about it for ourseleves.
<a name="work"></a> Work Organization & Contributions
This work is next divided into 2 parts as follows:
- Part 1: Datasets Exploration
- How did we obtain our data ?
- How did we choose our features ?
- How do we plan to use those features, and for which models ?
If you're interested to know more about this, head to data folder and datasets-notebooks.
- Part 2: Models Construction
- What are the models we used ?
- What are their Results ?
- Are they as expected, or we need to solve a credit assignment problem ?
If you're interested to know more about this, head to models-notebooks.
Our work contributions include the models we implemented to estimate both daily and total number of cases for countries and also the datasets we curated from multiple data sources. We open-sourced both on Github in the hopes of helping the community take one more step towards fighting COVID-19.
<a name="team"></a> Contributors & Acknowledgments
- Amr Elzawawy @Elzawawy
- Omar Wagdy @OmarWagdySalah
- Omar Swidan @oswidan97
- Mostafa Yousry @MostafaYousry
We acknowledge both Github & Kaggle communities that made this project possible by open-sourcing datasets and models that help leviate the COVID-19 danger and help to understand the problem more.