Understanding Subgroup Fairness in Machine Learning ML Evaluating fairness in machine learning often involves examining how models perform across different subgroups defined by attributes such
Introduction AI agents are increasingly moving from pure backend automators to visible, collaborative elements within modern applications. However, making agents genuinely interactive—capable of both responding
1. It with a Vision While rewatching Iron Man, I found myself captivated by how deeply JARVIS could understand a scene. It wasn’t just recognizing
In the first story [1] of this series, we have: Addressed multiplication of a matrix by a vector, Introduced the concept of X-diagram for a
If features powered by LLMs, you already know how important evaluation is. Getting a model to say something is easy, but figuring out whether it’s
The Challenge of Long-Context Reasoning in AI Models Large reasoning models are not only designed to understand language but are also structured to think through
to lead the cloud industry with a whopping 32% share due to its early market entry, robust technology and comprehensive service offerings. However, many users
isn’t yet another explanation of the chain rule. It’s a tour through the bizarre side of autograd — where gradients serve physics, not just weights
Boston – June 19, 2025 – Ataccama announced the release of a report by Business Application Research Center (BARC), “The Rising Imperative for Data Observability,”
Image by Editor | Midjourney While Python-based tools like Streamlit are popular for creating data dashboards, Excel remains one of the most accessible and