Abstract
A frequent business problem is discussed, whereby companies find themselves facing a large base of Unstructured Data, which proves cumbersome to process. A specific case is brought up in which the data arrives continuously from the users and is processed on the fly. A comprehensive approach to processing this Unstructured Data is discussed along with technical considerations.
Keywords: #ai #artificialintelligence #ml #machinelearning #python #nlp #csv #gpu #gcp #jupyter #docker #tensorflow
Problem statement
We seek an approach to handling Unstructured Data on the fly with Machine Learning techniques, particularly with Natural Language Processing.
Abstract
In this white paper we discuss building a piece of software which performs Creditworthiness Assessment based on hundreds of parameters included in loan applications for a popular motorcycle brand. The process involves creating an algorithm which calculates the risk associated with each loan. The goal is to suggest modifications to the loan application parameters, which would adjust them so that they represent good risk for the expected return.
Keywords: #python #optimization #lp #linearprogramming #credit #creditworthiness #calculation #numpy #scipy #sympy
Problem statement
As a creditor issuing loans for a popular motorcycle brand, we want to understand, whether a particular loan application represents good risk to us and, if not, how we can revert to the applicant with recommendations on how they can modify their application to pass our creditworthiness criteria.
Abstract
In this white paper we depict a problem occurring in Health Insurance, namely fraudulent claims. The challenge lies in sieving them out while retaining the legitimate ones. There are plenty of potential techniques for Fraud Detection, ranging from Supervised Learning to Unsupervised Learning. Due to the availability of abundant training data we decide to go with Supervised Learning in general and Deep Learning in particular. A number of technical considerations are discussed.
Keywords: #ai #artificialintelligence #ml #machinelearning #python #tensorflow #fraud #frauddetection #deeplearning #dnn
Problem statement
We want to define and implement an AI/ML-enriched process, which would enable us to detect fraudulent insurance claims and highlight them to relevant parties, who can take appropriate actions on them.
Abstract
The problem of face reenactment is discussed, i.e. the animation of a character provided in a stationary image. The animation follows the motion and the face expression found in a driving video. A solution is proposed and implemented to be readily accessible from an API and a web UI.
Keywords: #ai #generativeai #ml #machinelearning #computervision #gan #python #opencv #pytorch #aws #streamlit #fastapi
Problem statement
We want to develop a system that generates a synthetic video by animating a one-shot cartoon character image based on the motion and expressions from a driving video using state-of-the-art AI and Computer Vision techniques.