Machine learning is being used to learn more about the coronavirus pandemic, or COVID-19. By using machine learning algorithms, researchers can analyze large datasets of patient data to better understand the disease and identify possible treatments. For example, machine learning can be used to identify common symptoms of the disease accompanying the covid itself , predict outcomes for patients, and identify risk factors for severe illness. Machine learning can also help researchers better understand the long-term effects of the virus and the effectiveness of treatments. By utilizing machine learning, researchers can continue to improve our understanding of the virus and develop more effective strategies for fighting it.
dataset link on kaggle : https://www.kaggle.com/datasets/meirnizri/covid19-dataset
The dataset was provided by the Mexican government . This dataset contains an enormous number of anonymized patient-related information including pre-conditions. The raw dataset consists of 21 unique features and 1,048,576 unique patients. In the Boolean features, 1 means "yes" and 2 means "no". values as 97 and 99 are missing data.
In the "Covid_Visualizations_Preprocessig.ipynb" you can see preprocessing for the data to be able to use later.
The aim of the project is to visualize covid dataset to analyze it and see how some diseaes can affect the life of people. You can find this in Covid_Visualisations_Visualisations.ipynb
There is a dashboard created using PowerBI using the processed data for interactive visualizations.
For more information you can read the description added.