DocDigitizer (Organisation) Project
Industry
Intelligent Document Processing (IDP)
Skills
- Python
- R
- SQL
- Microsoft Azure
Algorithms
- Logistic Regression
- Decision Tree
Introduction
The objective of our project is to implement predictive modelling machine learning techniques to predict the achievability of Service Level Agreement (SLA) timelines for the documents that will be processed in future based on the factors that affect them. In the current data set, a small percentage of documents breached the SLA timeline and were not completed within that stipulated time due to different reasons. We developed a predictive system that will utilize algorithms to find out significant attributes (the reasons) from the data set which affect the SLA timelines of a document and further ingest them into our machine learning model. The implementation of classification algorithms along with feature selection techniques and hyper-parameter tuning of the attributes will help us build this predictive model to classify whether a document will be processed within their stipulated SLA timeline or not.