ML From Scratch
Machine Learning From Scratch. Bare bones NumPy implementations of machine learning models and algorithms with a focus on accessibility. Aims to cover everything from linear regression to deep learning.
Supply asset profile
Coding and developer agents
Code review, repo analysis, testing, CI, GitHub, DevOps, and developer workflow skills.
Scenario
GitHub automation
I need my agent to triage GitHub issues, review pull requests, and summarize repository changes.
Agent fit
Claude Code + CLI + Codex
Codex, Claude Code, Cursor, CLI, or custom agents.
Install
Ready
npx skills add eriklindernoren/ML-From-Scratch
Maintenance
stale
3y since push
Risk
Needs review
Repository appears stale
GitHub quality
32K
87/100 quality · 88/100 trust
Coverage tags
Review notes
Repository appears stale · Repository looks stale
Agent adoption scorecard
Trust, audit, and install readiness at a glance
These scores combine public repository metadata, OpenAgentSkill review signals, maintenance freshness, and install readiness. They are a shortlist signal, not a replacement for human review.
Quality
ExcellentHigh-confidence pick with strong adoption and healthy maintenance signals.
Trust
Production candidateStrong OpenAgentSkill Trust Score across adoption, recent maintenance, license clarity, documentation, dependency/runtime risk, install safety, permission surface, and install availability.
Audit
Needs reviewInstall readiness, security metadata, maintenance, and adoption risk.
Trust Score v3
Agent install candidate
Shortlist for production use, then run a normal repository and dependency review.
Stars
32K GitHub stars
Repo activity
32K stars, 5.3K forks
Maintenance
3y since push
License
MIT
Install
npx skills add eriklindernoren/ML-From-Scratch
Install safety
standard package or runtime install path
Permission surface
filesystem or document access
Docs
Strong README/SKILL.md context
Risk summary
Review before production
- Repository looks stale
- Recent maintenance: 3y since push
Install readiness
Install path available
- Install path is available
- Repository evidence is available
- License is declared
- 3y since push
Agent-readable metadata
Machine-readable decision data for this skill.
Use this block or the embedded JSON to decide whether an agent should install this skill, choose an alternative, or ask for human review first.
Suited tasks
- GitHub automation workflows
- Claude Code teams
- teams that value GitHub adoption signals
- Inspect repository metadata
- Compare code changes
Suited agents
Trust and risk
- Trust score
- 88/100
- Risk level
- Needs review
- Auto install
- review
Do not use when
- teams that require actively maintained dependencies
- production agents without a repository review
- Repository looks stale
- Repository appears stale
- Recent maintenance: 3y since push
Agent safety v2
63/100 · Review before install
Usable candidate, but the agent should surface permission and audit notes before installation.
Require human approval before installing into a real workspace.
medium
Network access
Skill likely fetches remote pages, APIs, repositories, or external services.
medium
Filesystem access
Skill may read or write project files, documents, generated artifacts, or local workspace state.
- Repository appears stale
Install targets
Install this skill in your agent workflow
Copy the registry command or an agent-specific install prompt for Codex, Claude Code, and Cursor.
OpenAgentSkill CLI
Use the registry command when your workflow supports the OpenAgentSkill installer.
$ npx skills add eriklindernoren/ML-From-ScratchAgent resolve plan
Let an agent verify fit before installing.
The Resolve API returns the selected skill, alternatives, safety policy, audit notes, install target, and copy-paste prompt an agent can follow without scraping this page.
Resolve JSON
/api/agent/resolve?task=Use%20ML%20From%20Scratch%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Resolve text
/api/agent/resolve?task=Use%20ML%20From%20Scratch%20for%20an%20agent%20workflow&agent=codex&max_risk=medium&format=text
Install handoff
/api/skills/eriklindernoren-ml-from-scratch/install
Agent should check
- Task fit and alternatives from Resolve API.
- Audit score, trust score, and safety policy warnings.
- Install target compatibility for Codex, Claude Code, Cursor, or CLI.
Copy prompt
Task: Use ML From Scratch in this workspace.
Resolve first: https://www.openagentskill.com/api/agent/resolve?task=Use%20ML%20From%20Scratch%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Review install handoff: https://www.openagentskill.com/api/skills/eriklindernoren-ml-from-scratch/install
Install command: npx skills add eriklindernoren/ML-From-Scratch
Before running it, summarize audit warnings, required permissions, and the fallback skill if install is risky.Agent handoff
Give an agent the install path, not another directory page.
Use the public install endpoint to fetch the command, safety checklist, target prompts, and canonical links for this skill.
Install handoff
/api/skills/eriklindernoren-ml-from-scratch/install
LLM text format
/api/skills/eriklindernoren-ml-from-scratch/install?format=text
Find alternatives
/api/skills/search?q=ML%20From%20Scratch&limit=3
Agent prompt
Use ML From Scratch for this task. Review https://www.openagentskill.com/api/skills/eriklindernoren-ml-from-scratch/install, then install with: npx skills add eriklindernoren/ML-From-ScratchRegistry metadata
Agent-readable profile for automatic skill selection.
This page exposes the same decision, trust, audit, use-case, and install signals through the Registry API, so agents can rank this skill without scraping the UI.
Manifest
/api/registry/manifest/eriklindernoren-ml-from-scratch
LLM text
/api/registry/manifest/eriklindernoren-ml-from-scratch?format=text
Install alias
/api/registry/install/eriklindernoren-ml-from-scratch
Recommend
/api/registry/recommend?task=Use%20ML%20From%20Scratch%20in%20an%20agent%20workflow&limit=3
Agent fit
GitHub automation
Use-case tags
Platforms
Python, Machine Learning, Claude Code
Audit report
Needs review · 79/100
Review install readiness, maintenance, trust, quality, and metadata warnings before adding this skill to an agent workflow.
Agent decision cockpit
Primary pick for GitHub automation
Use this as a leading candidate, then validate the README and install path in your own agent stack.
Role in stack
Primary pick
Primary fit
GitHub automation
Trust label
Production-ready
Install path
Command ready
Use when
- GitHub automation workflows
- Claude Code teams
- teams that value GitHub adoption signals
Evidence
- 31,915 GitHub stars
- install command or GitHub repo available
- 87/100 quality profile
- 1 OpenAgentSkill engagement events
Review first
- Repository looks stale
Implementation path
- 1Install it in a sandbox agent and run one GitHub automation task end to end.
- 2Compare output quality, latency, and failure behavior against at least one alternative.
- 3Promote it into production only after reviewing repository permissions, license, and maintenance signals.
Trust profile
Production candidate
Strong OpenAgentSkill Trust Score across adoption, recent maintenance, license clarity, documentation, dependency/runtime risk, install safety, permission surface, and install availability.
GitHub adoption
PASS32K GitHub stars
Stars/forks activity
PASS32K stars, 5.3K forks; issue activity unavailable in current metadata
Recent maintenance
FIX3y since push
License clarity
PASSMIT
Good signals
- Manually verified listing
- AI review approved
- Install path is available
- Repository evidence is available
- Large GitHub adoption signal
- Install command has no obvious high-risk pattern
Review before install
- Repository looks stale
- Recent maintenance: 3y since push
Recommended action
Shortlist for production use, then run a normal repository and dependency review.
Quality profile
Excellent candidate for agent workflows
High-confidence pick with strong adoption and healthy maintenance signals.
Workflow fit
Use this skill in these scenarios
Manage repositories
GitHub automation
I need my agent to triage GitHub issues, review pull requests, and summarize repository changes.
Build and ship code
Coding agents
I need a coding agent that can understand a repository, edit code, and review pull requests.
Search private knowledge
RAG and knowledge
I need my agent to build a RAG workflow over documents and retrieve reliable context.
Stack fit
Add it to a complete workflow
Turn skills into distribution
Content growth agent
A stack for turning newly indexed skills into SEO briefs, social drafts, comparison pages, and reusable publishing workflows.
Inspect, patch, and verify code
Coding review agent
A stack for software agents that inspect repositories, review pull requests, generate tests, and turn findings into shippable patches.
Ingest, retrieve, and cite
RAG knowledge base
A stack for document-heavy agents that ingest files, create searchable knowledge, retrieve relevant context, and answer with grounded sources.
Alternative shortlist
Compare before you install
Similar skills in this category, ranked with the same readiness and quality signals.
Tensorflow
An Open Source Machine Learning Framework for Everyone
Transformers
🤗 Transformers: the model-definition framework for state-of-the-art machine learning models in text, vision, audio, and multimodal models, for both inference and training.
Pytorch
Tensors and Dynamic neural networks in Python with strong GPU acceleration
LLMs From Scratch
Implement a ChatGPT-like LLM in PyTorch from scratch, step by step
Overview
Machine Learning From Scratch. Bare bones NumPy implementations of machine learning models and algorithms with a focus on accessibility. Aims to cover everything from linear regression to deep learning.
Imported by the skill-only GitHub discovery pipeline because it matches agent skill, automation, domain workflow, RAG, document-processing, data, finance, security, or developer-tool signals. Protocol-server projects are excluded from automated imports.
Platform Compatibility
Technical Details
- Version
- 1.0.0
- License
- MIT
- Last Updated
- 6/16/2026
- Published
- 6/16/2026
Frameworks & Tools
Decision snapshot
Primary pick
31,915 GitHub stars
Audit Snapshot
Install and adoption review
- Security
- 89/100
- Maintenance
- 20/100
- Install
- 92/100
Growth loop
Share this skill
Scenario-led draft for ML From Scratch, with the OpenAgentSkill Update theme and canonical URL.
OpenAgentSkill Update Today: ML From Scratch Use it when your agent needs to turn docs, data, or knowledge bases into answers and actions. 31.9K stars - ml-automation Link: https://www.openagentskill.com/skills/eriklindernoren-ml-from-scratch?ref=x #AIAgents #OpenAgentSkill
Optional reply with install command
Link for ML From Scratch: https://www.openagentskill.com/skills/eriklindernoren-ml-from-scratch?ref=x Install: npx skills add eriklindernoren/ML-From-Scratch
Listing source
Community indexed
This listing was indexed from public sources and is not marked official until a maintainer claim is approved.
- Creator
- eriklindernoren
- Indexed by
- OpenAgentSkill community index
Attribution links to the public repository or creator profile. Creators can claim the listing to update ownership signals.
Claim this skillOwner claim
Claim this skill listing
This community indexed listing is attributed to eriklindernoren but is not marked official yet. Claim it to add a verified owner signal and make future launch, install, and audit updates easier to trust.
README badge
Add this badge to your GitHub README to show the listing, trust score, and install handoff.
[](https://www.openagentskill.com/skills/eriklindernoren-ml-from-scratch)Author
eriklindernoren✓
@eriklindernoren
Tags
Platform Fit
Health Signals
- GitHub stars
- 31.9K
- Quality score
- 60/100
- Last GitHub push
- Oct 15, 2023
- Framework hints
- 2
- OpenAgentSkill views
- 1
- Install copies
- 0
- Outbound clicks
- 0
Community Signal
Share whether this skill looks useful for your agent workflow. Aggregated feedback improves rankings over time.
Trust & Safety
Production candidate
- GitHub adoption32K GitHub starsPASS
- Stars/forks activity32K stars, 5.3K forks; issue activity unavailable in current metadataPASS
- Recent maintenance3y since pushFIX
- License clarityMITPASS
- README/SKILL.md completenessMetadata includes enough usage and workflow contextPASS
- Dependency/runtime riskno major dependency risk hints in public metadataPASS
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