Non-QM Bank Statement Mortgage: An Overview What is a Non-QM Mortgage? A Non-Qualified Mortgage (Non-QM) is a mortgage product that falls outside the regulatory definitions of a “Qualified Mortgage” under CFPB rules, meaning it allows more flexible underwriting and documentation standards. These loans are often used by borrowers who have valid income but cannot …
Category: AI ML NLP DL
NonQM Underwriter
Excellent — let’s now focus specifically on the Post-Close Non-QM Underwriter role — which combines traditional post-closing QC review with the manual-credit, non-agency, and investor-specific compliance nuances of Non-Qualified Mortgage (Non-QM) lending. Below is a full, structured breakdown of what a Post-Close Non-QM Underwriter does, their workflow, tools, and investor QC requirements — all sourced …
Google Photos to YouTube automation
This project is for google photos to upload automatically to youtube as video, so, it takes approx 50 or 100 photos or can be customized to take 1GB photos collections automatically and then create a slideshow, upload to youtube as unlisted or private video and delete photos automatically so you dont have to worry about …
Explore connections and runtimes – AI ML LLM
When you create a Large Language Model (LLM) application with prompt flow, you first need to configure any necessary connections and runtimes. Explore connections Whenever you want your flow to connect to external data source, service, or API, you need your flow to be authorized to communicate with that external service. When you create a connection, you configure a …
Facial recognition with Deep Learning
Advanced Deep Learning and Computer Vision Objective: Create a facial recognition tool using a relevant deep learning algorithm, leveraging the provided resources. Context: An American AI company that has developed a healthcare app for doctors. The app utilizes deep learning algorithms to aid in diagnosing patients for genetic disorders and their variants. …
Preserving Heritage: Enhancing Tourism with AI – Capstone project
There are centuries old historical structures that preserve a country’s and community’s history for future generations and promote tourism opportunities. To improve tourism, a government agency decides to use advanced machine learning techniques to monitor the condition of these historical structures and report if any of them need maintenance. Also, understanding customers (tourists) and their …
Use AI to read credit report in efolder and push credit report generation date to field 5040 in encompass
Creating an Encompass plugin that reads a PDF from the eFolder, uses AI to detect the Credit Report generation date, and writes that date to Field 5040 involves a combination of: Encompass Plugin SDK / API PDF parsing (AI/NLP or regex for credit reports) Integration with an OCR/AI engine Writing values to loan fields Overview …
Lending club Loan data analysis with Keras and TensorFlow – AI Project for Loans Data
Deep Learning with Keras and TensorFlow Project – Lending Club Loan Data Analysis Objective: Create a model that predicts whether or not a loan will be default using historical data. Problem Statement: For companies like Lending Club correctly predicting whether or not a loan will be a default is very important. In this project, using …
Sales Analysis Project in AI Python Panda Sklearn scikit-learn matplotlib dash core Write up
All correct packages like pandas, scikit-learn, matplotlib, seaborn, dash, dash core components and html etc should be installed using pip install Since this project is going to be saved as a Jupyter notebook file so csv file must be placed in same directory where the notebook .ipynb is saved. Although it can be saved …
Employee turnover project with ML Panda Python Artificial Intelligence AI
Problem statement Portobello Tech is an app innovator who has devised an intelligent way of predicting employee turnover within the company. It periodically evaluates employees’ work details, including the number of projects they worked on, average monthly working hours, time spent in the company, promotions in the last five years, and salary level. Data …
