About

Welcome to our data science project! Our goal is to explore and visualize the COVID-19 dataset and use machine learning to predict PCR outcomes. Our project leverages the power of R, R Studio, h2o, plotly, and tidyverse to make the data analysis process fast, intuitive, and insightful.

The COVID-19 pandemic has affected the entire world in unprecedented ways, and this dataset provides valuable insights into the spread of the virus, its impact on healthcare systems, and the effectiveness of interventions. Our project focuses on the PCR outcome, which is a binary variable indicating whether a person tested positive or negative for COVID-19. With 33 features, this dataset offers a wealth of information that we can use to build a predictive model and gain a better understanding of the factors that influence PCR outcomes.

Our approach to data analysis involves two main steps: visual exploration and machine learning. In the first step, we use plotly to create interactive plots that allow us to visualize the relationships between the features and the PCR outcome. These plots reveal patterns and correlations that would be difficult to detect with traditional statistical methods. We use the tidyverse package to preprocess the data and make it suitable for visual exploration and modeling.

In the second step, we use h2o’s autoML functionality to build a machine learning model that predicts PCR outcomes. AutoML automates the model selection and hyperparameter tuning process, allowing us to focus on the more important task of interpreting and validating the results. We evaluate the model’s performance using metrics such as accuracy, precision, recall, and F1 score. We also use techniques such as cross-validation and feature importance to ensure that the model is robust and generalizable.

Our project demonstrates the power of data science in addressing real-world problems. By using visual exploration and machine learning, we can gain a deeper understanding of the COVID-19 dataset and make predictions that have real-world implications. We hope that our work will inspire others to use data science to solve important problems and make a positive impact on society.

In conclusion, our data science project combines the power of R, R Studio, h2o, plotly, and tidyverse to explore and analyze the COVID-19 dataset. We use visual exploration and machine learning to gain insights and make predictions about PCR outcomes. Our project demonstrates the potential of data science to address complex problems and contribute to the common good.