The client is an over 150-year-old, nationally recognized banking institution with hubs in Kansas City and St. Louis. A team of seven Keyhole consultants was brought in to assist this client in the development of a React web application designed to help hospitals and clinics manage bills and payments. The team worked in conjunction with the client’s development team and …
Client Snapshot A large, North American engineering and construction organization operating at enterprise scale, supporting complex, mission-critical systems across multiple business units. Engagement Overview Keyhole Software partnered with this organization to support and modernize its cloud and data platforms across multiple concurrent engineering teams. A Principal Consultant worked alongside internal stakeholders to strengthen Azure architecture, improve data platform performance, and …
In my last blog post Back in the Groovy 4, I briefly mentioned Groovy-Integrated Query (GINQ). I’ve been wanting to write about how I would use this new feature, and I decided to take this opportunity to do so.
In this post, I will be describing two examples in which I used GINQ. The first requirement I faced on a recent project of mine and demonstrating how I used GINQ to fulfill it. A quick disclaimer: this is not a tutorial on GINQ. This blog is merely a discussion of how I’ve used GINQ and how I plan on making it part of my toolkit.
In this video, Alex presents an introduction to data science “big ideas” relevant to the model, an explanation of its data modeling process, and a demonstration of the real-life machine learning solution implemented with Python, Postgres SQL, and H2O (an open-source machine learning algorithm). Multiple data sources and technologies were combined to create an accurate model that allows farmers and recreationists to make actionable insights about the future. A few questions and answers round out the discussion.
Data Science / Data Mining Supervised Learning Time-Series ModelHome→Search ResultsThis 42-minute video provides a technical breakdown of a supervised learning time-series model that uses data science to make predictions of the daily water flow of the Norfork River.RecordingThe recording was taken at a Keyhole Software Employee Lunch & Learn in May 2022. There are other applications of data science and …