Scikit-learn Reviews

ast-grep Reviews

Scikit-learn mentions (40)

• Detecting Ingress Tool Transfer (T1105) with Python

  Certutil.exe or notepad.exe opening an external connection lands in rare because, fleet-wide, those processes almost never egress. Tune the <= 3 threshold to your environment size. For a more principled version, score each (process, destination) pair by frequency and treat the long tail as the hunt queue, which is the same idea behind scikit-learn's rarity-based anomaly methods without the model overhead. - Source: dev.to / about 1 month ago

• Best AI Cybersecurity Training for Security Teams: How to Pick

  Pre-configured environment. A working VM or container with Jupyter, pandas, scikit-learn, and transformers already installed. Realistic security datasets loaded. GTK Cyber students work in the Centaur VM, a free Apache 2.0 portable lab. If the first hour of training is fighting CUDA installs, the course is not ready. - Source: dev.to / about 2 months ago

• Where to Get Hands-On AI Training for Cybersecurity Professionals

  Pre-configured environment. A good course ships a VM or container with Jupyter, pandas, scikit-learn, PyTorch or transformers, and realistic security datasets loaded. GTK Cyber students work in the Centaur VM, a free Apache 2.0 portable lab. No setup tax. - Source: dev.to / about 2 months ago

• How Anomaly Detection Actually Works in Security Operations

  Isolation-based models: Build random decision trees that split features. Points that are isolated quickly (short average path length across trees) are anomalies. IsolationForest in scikit-learn implements this. Handles high-dimensional feature spaces without assuming a distribution. - Source: dev.to / 3 months ago

• Building a Personalized Meal Recommendation System

  In practice, you’ll want to use libraries (like scikit-learn or TensorFlow.js for more advanced modeling), but the principle remains: find what similar users enjoy, and use that as a basis for recommendations. - Source: dev.to / 4 months ago

ast-grep mentions (24)

• The Self-Driving Codebase: Full Agent Automation with Otter

  The previous post covered how we structured the codebase: Effect conventions, ast-grep enforcement, Drift, and CLAUDE.md to collaborate with Claude Code. You describe what you want, review the output, iterate. That works well. This post is about what happens when you step away entirely: giving the agent a list of issues and letting it work through them while you do something else. In autonomous mode, there's no... - Source: dev.to / 2 months ago

• How we use Effect and ast-grep to make our codebase work better with agents

  We use ast-grep as a structural syntax scanner that operates on the syntax tree of code (using tree-sitter under the hood). You define patterns in a YAML file, and it matches those patterns against the codebase. Critically, it’s run as part of the CI pipeline and configured to exit with an error when a banned pattern is found. And they have to be errors, not warnings. We learned this the hard way. Warnings get... - Source: dev.to / 2 months ago

• Less human AI agents, please

  I linked this elsewhere but, the agent could have a skill to use https://ast-grep.github.io/ to perform such mechanical code changes. - Source: Hacker News / 3 months ago

• Less human AI agents, please

  The proper tool for this is ast-grep (sg) https://ast-grep.github.io/ And an agent can learn to use sg with a skill too. (Or they can use sed) The issue is, at every point you do a replace, you need to verify if it was the right thing to do or if it was a false positive. If you are doing this manually, there's the time to craft the sed or sg query, then for each replacement you need to check it. If there are... - Source: Hacker News / 3 months ago

• Be intentional about how AI changes your codebase

  We use https://ast-grep.github.io (on a pre-commit hook). Bridges the linter gaps nicely. - Source: Hacker News / 4 months ago