Predicting-Patient-Readmission-Within-30-days

• EDA, Visualization
• Feature Engineering based on the descriptions given in the pdf.
• Label Encoding.
• Removing Univariate columns, Checking Chi-square test of independence, f-classif and VIF for better insights.
• Splitting the data into train, validation and test sets, Imputating, standardizing, One Hot Encoding the data.
• Defining confusion matrix and classification report.
• Building Neural Network using TensorFlow Sequential API.
• Fitting the model and finding the error metrics on train, validation and test datas.