Using Datawig, an AWS Deep Learning Library for Missing Value Imputation - KDnuggets

While training a Machine Learning model the quality of the model is directly proportional to the quality of data. However, in some cases, there are a lot of missing values in the dataset affecting the quality of prediction in the long run. Several methods can be used to fill the missing values and Datawig is one of the most efficient ones. Datawig is a Deep Learning library developed by AWS Labs and is primarily used for "Missing Value Imputation". The library uses "mxnet" as a backend to train the model and generate the predictions.