A new Visual Studio Code extension called Nogic sparked a wide-ranging Hacker News discussion, with commenters praising its ...

The research fills a gap in standardized guidance for lipidomics/metabolomics data analysis, focusing on transparency and reproducibility using R and Python. The approach offers modular, interoperable ...

Prerequisite: Introduction to Python for Absolute Beginners or some experience using Python. You’ve cleaned and analyzed your data, now learn how to visualize it. Visualizing data is critical for both ...

Implement a feature that visualizes rule dependency graphs in the RulesEngine administration portal and/or API. This will help users understand how rules and workflows interconnect, making it easier ...

The cloud SIEM is gaining long-term data lake log storage, AI graph visualization, support for MCP, and a way to interact with custom agents built in Security Copilot, but it’s unclear yet whether ...

Fifteen years ago, I introduced the zero-trust security model while working as an analyst at Forrester Research. At the time, cybersecurity was still rooted in perimeter-based thinking, built on the ...

In this tutorial, we explore how we can seamlessly run MATLAB-style code inside Python by connecting Octave with the oct2py library. We set up the environment on Google Colab, exchange data between ...

Python developers often need to install and manage third-party libraries. The most reliable way to do this is with pip, Python’s official package manager. To avoid package conflicts and system errors, ...

@coleam00 @Wirasm While working on PR #254, I came across a few questions about some of the architectural choices in the project: I’m curious about the decision to have a backend. Since Supabase is ...

Abstract: Dependency Graph (DG) structural pruning for enabling edge deployment of optimized Deep Learning (DL) models within the context of Non-Intrusive Load Monitoring (NILM) is introduced. DG ...