presentation

https://prezi.com/p/dj_zluhaqhgz/chasers-of-lost-data/

Data in the real-world are rarely clean. The easiest way is to remove the missing data. However, there are hidden patterns in them. Our idea is to infer those missing values from the existing part of the data. Therefore, we get the relationship between the data and then impute the missing values using the most contributing ones.We tried different imputation methods and chose the best of them according to accuracy ,speed and scalability. Also we visualized the distribution of data before and after imputation

https://github.com/Nada-ibrahim/Handlny-Imputation-Package