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Predicting Risk of Death from analysed Patient Data

Studying_Reactions_To_VACCINES

An Exploratory Data Analysis and Machine Learning model

This Notebook contains scrupulous data analytics which involves:

• Extensive Data cleaning, wrangling, analysis and visualizations
• Building working Machine Learning models with high predictive capabilities
• Using proper computational algorithms and visualizations to derive insights from real-world Data ( i.e. Who is more likely to develop adverse reactions to vaccination )
• Involves an interactive session where we apply our Machine Learning Model to answer tough questions ( i.e. Given a case note report of individual patient bio-data and clinical history, we'd use our model to predict those who are likely to survive adverse reactions to COVID19 vaccination? )
• Key graphs on survivor demographics are in place

Datasets Used in this repository

The datasets used in this repository comes from the following source - https://www.kaggle.com/ayushggarg/covid19-vaccine-adverse-reactions under a CC0: Public Domain license (https://creativecommons.org/publicdomain/zero/1.0/)