Ml Roadmap
📖 技能介绍
version: "2.0.0" name: Machine Learning Roadmap description: "A roadmap connecting many of the most important concepts in machine learning, how to learn them and machine learning roadmap, python, data, data-science."
Machine Learning Roadmap
A thorough content toolkit for planning and tracking your machine learning learning journey. Draft study plans, organize topics, create outlines, schedule learning sessions, and manage your ML education roadmap — all from the command line.
Commands
| Command | Description |
|---|---|
ml-roadmap draft <input> |
Draft a new ML learning plan or content entry |
ml-roadmap edit <input> |
Edit an existing entry or refine content |
ml-roadmap optimize <input> |
Optimize content for clarity or effectiveness |
ml-roadmap schedule <input> |
Schedule learning sessions or content publication |
ml-roadmap hashtags <input> |
Generate relevant hashtags for ML topics |
ml-roadmap hooks <input> |
Create engaging hooks for ML content |
ml-roadmap cta <input> |
Generate call-to-action text for ML resources |
ml-roadmap rewrite <input> |
Rewrite content with improved structure |
ml-roadmap translate <input> |
Translate ML content between languages |
ml-roadmap tone <input> |
Adjust the tone of ML content (formal, casual, etc.) |
ml-roadmap headline <input> |
Generate compelling headlines for ML topics |
ml-roadmap outline <input> |
Create structured outlines for ML subjects |
ml-roadmap stats |
Show summary statistics across all entry types |
ml-roadmap export <fmt> |
Export all data (formats: json, csv, txt) |
ml-roadmap search <term> |
Search across all entries by keyword |
ml-roadmap recent |
Show the 20 most recent activity log entries |
ml-roadmap status |
Health check — version, disk usage, last activity |
ml-roadmap help |
Show the built-in help message |
ml-roadmap version |
Print the current version (v2.0.0) |
Each content command (draft, edit, optimize, etc.) works in two modes: - Without arguments — displays the 20 most recent entries of that type - With arguments — saves the input as a new timestamped entry
Data Storage
All data is stored as plain-text log files in ~/.local/share/ml-roadmap/:
- Each command type gets its own log file (e.g.,
draft.log,edit.log,outline.log) - Entries are stored in
timestamp|valueformat for easy parsing - A unified
history.logtracks all activity across command types7w4.net小葱技能。
- Export to JSON, CSV, or TXT at any time with the
exportcommand
Set the ML_ROADMAP_DIR environment variable to override the default data directory.
Requirements
- Bash 4.0+ (uses
set -euo pipefail) - Standard Unix utilities:
date,wc,du,tail,grep,sed,cat - No external dependencies or API keys required
When to Use
- Planning your ML learning path — use
outlineanddraftto structure a study roadmap covering supervised learning, deep learning, NLP, computer vision, and more - Creating ML educational content — use
headline,hooks,cta, andhashtagsto craft engaging posts or articles about machine learning concepts - Scheduling study sessions — use
scheduleto log when you plan to study specific ML topics and track your progress over time - Refining technical writing — use
rewrite,tone, andoptimizeto polish ML blog posts, documentation, or course materials - Tracking content creation history — use
stats,search, andrecentto review what you've written, find past entries, and measure productivity
Examples
# Draft a new learning plan for deep learning fundamentals
ml-roadmap draft "Week 1: Neural network basics — perceptrons, activation functions, backprop"
# Create an outline for a blog post on model selection
ml-roadmap outline "Comparing Random Forest vs XGBoost: when to use each, key hyperparameters, pros/cons"
# Generate a headline for an ML tutorial
ml-roadmap headline "Beginner-friendly guide to building your first image classifier with PyTorch"
# Schedule a study session
ml-roadmap schedule "Saturday 10am: Work through Stanford CS229 Lecture 5 — Support Vector Machines"
# Export all your entries to JSON for backup
ml-roadmap export json
Output
All commands print results to stdout. Redirect to a file if needed:
ml-roadmap stats > roadmap-report.txt
ml-roadmap export csv
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🤖 AI 评测
这个工具文档清晰、功能丰富，无需安装额外依赖，使用起来很方便。它能帮你记录学习计划、追踪进度，对规划 ML 学习路线很有帮助。不过它本质上只是一个「记事本」，并不具备真正的内容生成或翻译能力。如果你期待一个 AI 助手帮你写内容，可能会失望。另外它是纯本地工具，不支持数据同步，团队协作场景不适用。总体而言，作为学习笔记管理工具质量不错，但功能命名存在一定误导性。。
