README.md

forecasting-COVID19-vaccines

Forecasting COVID-19 Vaccines Trend with Deep Learning Technique

How to Usage

Please, connect with Google Colab or Jupyter Notebook with provided Dataset

1. Forecast_COVID-19_Vaccines_ARIMA

Dataset: Country Vaccinations

List of Code:

1. Exploration Data Analysis including Vaccination Count, Total Vaccination, etc
2. Forecasting Depend on Highest Vaccine Used
3. Future Prediction and Comparison
4. Evaluation Metrics

2. Forecast_COVID-19_Vaccines_LSTM

Dataset: Country Vaccination, Countries Aggregated

List of Code:

1. Exploration on Each Country
2. Forecasting Depend on Specific Country (e.g. in this experiment take Indonesia)
3. Future Prediction and Comparison
4. Evaluation Metrics

3. Forecast_COVID-19_Vaccines_LR

Dataset: Country Vaccination, Countries Aggregated

List of Code:

1. Exploration Data on Total Vaccination Depend on Country, Corelation Heatmap, etc
2. Prediction Section Depend on Highest Vaccine Used
3. Prediction over next 30, 60, 90 days
4. Evaluation Metrics

4. Forecast_COVID-19_Vaccines_Prophet

Dataset: Country Vaccination, Gapminder Tidy

List of Code:

1. Exploration Data on Classification of Region Vaccine
2. Forecasting Prediction Depend on People Fully Vaccinated per Hundred
3. Evaluation Metrics
4. Fix for Forecasting in Prophet Depend on Daily Vaccination
5. Trend and Weekly Data

Evaluation Metrics

This file provided in Excel format

Credit

This repository dedicated to research experiment on data science related Covid-19

Proposed Paper

Forecasting Covid-19 Vaccine Trends with Deep Learning Depending on the Type of Vaccine Used