During this project, I was involved in creating a full stack web-based product thereby developing a deep understanding of all aspects of product development such as identifying appropriate user requirements, designing a great user experience and building appropriate data models and machine learning models along with relevant UI components and backend design.
The purpose of the Ml project is used to predict the expected date of the due amount to be paid for the owner of the company in an invoice data
This ML project is used to predict the invoice pending date, We have provided a huge amount of invoice data which is unfiltered and consists of null and missing values which is not preferred for data analysing so for data preprocessing i have imported the data in the form of CSV file to Jupiter notebook later I have performed data preprocessing by removing the null values and missing values and plotted a box plot for determining the outliers in the data after plotting the graph The outliers has been determined and I have removed from the data, later I have splitted the data into train and test data and took the test data and applied the different types of regressions models on it and found the r2 score and mean root square error and choosed the regression model which has less mean square error then I have feeded the model with some data and applied the regression model on to the test data and created a new column name aging bucket which consists of the predicted date for peding due of clearing amount.