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Homemade Machine Learning Skill

Name: Homemade Machine Learning Skill
Author: bytesagain-lab

作者 bytesagain-lab · GitHub ↗ · v1.0.1 · MIT-0

cross-platform ✓ 安全检测通过

196

总下载

当前安装

版本数

在 OpenClaw 中安装

/install homemade-machine-learning-skill

功能描述

Machine learning skill: find, explain, and implement ML algorithms with interactive Jupyter Notebook links. Covers linear regression, logistic regression, ne...

使用说明 (SKILL.md)

Homemade Machine Learning Skill

Machine learning skill: learn, explain, and implement ML algorithms from scratch. Based on trekhleb/homemade-machine-learning (MIT, 22k+ ⭐)

📦 Install: clawhub install homemade-machine-learning-skill

5 algorithms · 11 interactive notebooks · math explained · Python code included

Commands

explain — 解释算法原理 + 数学 + 代码

bash scripts/ml-notebook-finder.sh explain "linear regression"
bash scripts/ml-notebook-finder.sh explain "neural network"
bash scripts/ml-notebook-finder.sh explain "kmeans"

notebook — 获取交互式 Jupyter Notebook 链接

bash scripts/ml-notebook-finder.sh notebook "logistic regression"
bash scripts/ml-notebook-finder.sh notebook "anomaly detection"

code — 获取 Python 实现代码片段

bash scripts/ml-notebook-finder.sh code "linear regression"
bash scripts/ml-notebook-finder.sh code "kmeans"

path — 生成学习路径（按难度排序）

bash scripts/ml-notebook-finder.sh path beginner
bash scripts/ml-notebook-finder.sh path intermediate
bash scripts/ml-notebook-finder.sh path advanced

list — 列出所有算法

bash scripts/ml-notebook-finder.sh list

Algorithms

Algorithm	Type	Notebooks	Use Case
linear regression	supervised	3	price prediction, forecasting
logistic regression	supervised	4	classification, MNIST
neural network (MLP)	supervised	2	image recognition, deep learning
k-means	unsupervised	1	clustering, segmentation
anomaly detection	unsupervised	1	fraud detection, monitoring

Source

MIT License — Original author: trekhleb Indexed by BytesAgain — AI skill discovery platform

安全使用建议

This skill appears to be a benign educational helper that prints algorithm explanations, Python snippets, and links to public GitHub/nbviewer notebooks. Before installing, review the included script (scripts/ml-notebook-finder.sh) yourself — it is plain shell and only prints text and URLs. When you follow the notebook links, remember they point to external content (GitHub / nbviewer); review any external notebooks before running code from them. Do not supply secrets or credentials to this skill (it does not need any). If you want to be extra cautious, run the script in a restricted environment or inspect its full output before using linked notebooks.

功能分析

Type: OpenClaw Skill Name: homemade-machine-learning-skill Version: 1.0.1 The skill is an educational resource for machine learning, providing explanations, code snippets, and links to Jupyter notebooks. The primary script scripts/ml-notebook-finder.sh functions as a static information retriever and does not perform any network operations, file system changes, or command execution beyond printing text.

能力评估

✓ Purpose & Capability

Name/description promise (explain algorithms, provide notebooks and code) matches the provided SKILL.md and the included shell script, which resolves queries and prints explanations, snippets, and links to trekhleb's GitHub and nbviewer.

✓ Instruction Scope

Runtime instructions direct the agent/user to run the local script with specific subcommands (explain, notebook, code, path, list). The script only reads its CLI args and prints content/URLs; it does not attempt to read unrelated files, environment variables, or transmit data to unexpected endpoints.

✓ Install Mechanism

No install spec is provided (instruction-only plus a shipped script). Nothing is downloaded or written to disk by an installer; the included script is plain shell and not obfuscated.

✓ Credentials

No environment variables, credentials, or config paths are required. The skill does not request tokens or secrets and only references public GitHub/nbviewer URLs.

✓ Persistence & Privilege

always is false, agent invocation is normal default, and the skill does not modify other skills or system config. It has no elevated persistence or system-wide privileges.

如何使用

确保已安装 OpenClaw（本地或 Docker 部署）
在对话框中输入安装命令：/install homemade-machine-learning-skill
安装完成后，直接呼叫该 Skill 的名称或使用 /homemade-machine-learning-skill 触发
根据 Skill 的参数说明提供必要输入，即可获得结构化输出

版本历史

v1.0.1

Fix: tone down bytesagain attribution, keep it natural

v1.0.0

Launch: ML algorithm explainer with math, Python code, Jupyter notebooks, and learning paths

元数据

Slug homemade-machine-learning-skill

版本 1.0.1

许可证 MIT-0

累计安装 0

当前安装数 0

历史版本数 2

常见问题