Scikit-learn Reviews

opencode 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 / 2 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

opencode mentions (67)

• ZCode: Claude Code from the Makers of GLM

  Https://opencode.ai/ OpenCode was the first agent harness I used, and I have always like it. You can configure a wide variety of providers, but it's open source and has a number of core contributors. The other opinionated option is Pi (the Pi agent harness). This is a great lightweight option and also supports a number of providers. You can also use local model servers. - Source: Hacker News / 2 days ago

• AI for Less Popular Programming Languages

  OpenCode with GLM 5.2 wrote custom Emacs Lisp to pinpoint within the file where the missing or extra bracket could be. It rewrote the custom code to check various parts of the file. Each of those is a tool use and many, many tokens burned. The next step is to turn those custom scripts written by the AI agent into a tool to speed up the process, or a skill that shows how to use other tools to speed up the process. - Source: dev.to / 5 days ago

• How to Run Reliable Local LLM Agents on an RTX 3090: A Benchmark (5 Models, Priced in Watts)

  I gave GLM-4.5-Air (106B, open weights) 12 coding tasks through opencode on my RTX 3090. It scored 0% — never edited a single file. - Source: dev.to / 6 days ago

• The head chef model of AI collaboration

  Set up your stations. I work in two Ghostty terminals. The left side is for planning and viewing, the right for synchronous agents running through OpenCode. - Source: dev.to / 15 days ago

• Testing GLM-5.2 on OpenCode: I'm impressed!

  If you want to try it yourself: grab OpenCode, point it at OpenRouter, select GLM 5.2, and give it a real task instead of a benchmark. The z.ai docs have the rest of the details. - Source: dev.to / 16 days ago