Longitudinal Image-based AI Models for Health and Medicine Key Points, TLDR: The combination of body composition imaging and meta-data (e.g. age, sex, grip strength, walking speed, etc) resulted in the best 10 year mortality predictions Longitudinal or se- 26735Murphy2025-03-23
Use these text extraction techniques to get quality data for your LLM models- 20169Murphy2025-03-23
Thanks to Prof. Yaron Senderowicz and Liav Isaac Shopen for their willingness to be interviewed for this blog post. Intro and Motivation DALL·E2 has been out for a while, and I thought it could be interesting to write a blog post about it from a philosoph- 24154Murphy2025-03-23
Background I’m sure you’ve seen the series of images of a galloping horse by 19th-century English photographer Eadweard Muybridge. As a refresher, here is a GIF animation that shows one of his more famous photo series. And here’s a portr- 22541Murphy2025-03-23
How to leverage OpenAI GPT-4 Functions to navigate your GUI- 23348Murphy2025-03-23
Handling seasonal effects in several periods- 24836Murphy2025-03-23
A Tale of AI and wrongly-classified Brazilian Federal Laws- 28787Murphy2025-03-23
Introduction Imagine a Report page with some Cards, columns, and line charts. On top of the page, you will see four buttons: Actuals YTD (Year-To-Date) YE (Year-End) Last three months Something like this: When you click on the Button YTD, your numbers wil- 29893Murphy2025-03-23
Understand and master OCR tools for text localization and recognition- 24322Murphy2025-03-23
The story discusses the solution to the racetrack exercise in the Reinforcement Learning book together.- 23502Murphy2025-03-23
MIT Calls this "the missing semester of your CS education"- 29745Murphy2025-03-23
Beyond Basics: Advanced Python Exception Testing for Pytest and Unittest- 21231Murphy2025-03-23
Most organizations of a given size and age have by now kicked off an initiative to enhance the way they treat and manage data. Any attempt to structurally enhance data management capabilities will require a minimum amount of centralization, if only to dis- 26948Murphy2025-03-23
An In-Depth Exploration: Open vs Closed Source LLMs, Unpacking Llama 2's Unique Features, Mastering the Art of Prompt Engineering, and...- 20192Murphy2025-03-23
This article explained the pandas' methods for time series. Let's deal with the time series like a pro.- 27397Murphy2025-03-23
Build scalable and fast data pipelines with Polars- 29565Murphy2025-03-23
Dive into combinations of LSH functions to guarantee a more reliable search- 20449Murphy2025-03-23
Data engineers discovered the benefits of conscious uncoupling around the same time as Gwyneth Paltrow and Chris Martin in 2014. Of course, instead of life partners, engineers were starting to gleefully decouple storage and compute with emerging technolog- 22635Murphy2025-03-23
From planning to execution - how I built GPT lab- 28202Murphy2025-03-23
Introduction Am I the only one who periodically gets confused when dealing with dimensions in NumPy? Today, while reading a Gradio’s documentation page, I came across the following code snippet: sepia_filter = np.array([ [0.393, 0.769, 0.189], [0.34- 24722Murphy2025-03-23
Why is ChatGPT only trained up until 2021?
Learn how to rearrange your code to achieve significant speed improvements.
