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TOOLS = { “calc”: lambda expression: _safe_calc(expression), “kb_search”: lambda query, k=3: _kb_search(query, int(k)), “extract_json”: lambda text: _extract_json(text), “write_file”: lambda path, content: _write_file(path, content), } TOOL_SCHEMAS =…

In the world of data science, SQL still remains the powerful tool for defining the data, data manipulation, data aggregation and data analysis. While basic SQL…

Image by Author   # Introduction  Most data scientists learn pandas by reading tutorials and copying patterns that work. That is fine for getting started, but it…

In this tutorial, we explore how to run OpenAI’s open-weight GPT-OSS models in Google Colab with a strong focus on their technical behavior, deployment requirements, and…

Image by Author   # Introduction  Data validation doesn’t stop at checking for missing values or duplicate records. Real-world datasets have issues that basic quality checks miss…

Computer Vision remains one of the most commercially valuable areas in AI. Powering applications from autonomous driving to medical imaging and generative systems. But breaking into…

Image by Editor   # Introduction  Google NotebookLM has evolved far beyond a simple study aid. With the addition of the recent updates pushed just this year,…

In this tutorial, we explore how to use Google’s LangExtract library to transform unstructured text into structured, machine-readable information. We begin by installing the required dependencies…

In 1995, Windows was everywhere. It was also, let’s be kind, a little fragile. You didn’t use Windows back then so much as you negotiated with…

In this tutorial, we build and explore the CAI Cybersecurity AI Framework step by step in Colab using an OpenAI-compatible model. We begin by setting up…