Hands-on AI and machine learning tutorials in Python: model building, computer vision, NLP, and practical code guides.
The sphere of Natural language processing or NLP has undergone inspiring breakthrough due to the incorporation of state-of-art deep learning techniques. These algorithms have improved the internal flexibility of NLP…
THE GIST ▸ What it is: A 3,826-line system prompt steering Claude Fable 5 inside the Claude app, pulled from a public GitHub archive. ▸ What’s in it: Rules about…
# Introduction Large language model (LLM) apps get slow and expensive faster than you’d expect. In a prototype, things look fine. A few users, one model call, a short prompt,…
Open vocabulary segmentation lets you segment any object you can describe in text, like “door”, with no labeled dataset, fixed class list, or training: SAM 3 returns pixel-level masks for…
, someone at work brings up a version of this question: is AI going to take my job? I’ll admit that I have asked some version of that same question…
The GPU memory hierarchy is increasingly becoming an area of interest for deep learning researchers and practitioners alike. By building an intuition around memory hierarchy, developers can minimize memory access…
Prompts shape every interaction with a large language model. Clear instructions produce focused, useful responses, while vague ones often lead to inconsistent results. This becomes harder when teams need the…
# Introduction When you open Gemini CLI, describe a feature you need to build, and the agent immediately starts writing code. No questions, no clarifications, no plan. Ten minutes later,…
In this article, you will learn how to evaluate LLM applications using the three dominant open-source frameworks — RAGAS, DeepEval, and Promptfoo — and why the LLM-as-a-judge mechanism they all…
Video process monitoring automates the extraction of actionable operational data such as object counts, throughput, and speed, from raw camera feeds without requiring manual observation. By combining RF-DETR for object…
