Azure AI/ML for Python β manage Azure ML workspaces, jobs, models, datasets, compute, pipelines
π³ Paid API required β Azure subscription billed. Work the Azure Machine Learning SDK v2 in Python: MLClient auth, workspaces, data assets, model registry, compute clusters, command jobs, pipelines, environments, datastores
- What
- π³ Paid API required β Azure subscription billed. Work the Azure Machine Learning SDK v2 in Python: MLClient auth, workspaces, data assets, model registry, compute clusters, command jobs, pipelines, environments, datastores
- Cost
- Free
- Needs
- an Azure subscription (billed β compute, job runs, and storage cost real money), Python, and your Azure credentials (never hardcode them)
- Install
- Copy the installer prompt below into your Muse β your agent does the rest.
Curated by Skill Harbor β π³ Paid API required: real use needs an Azure subscription β compute clusters, job runs, and storage are billed by Microsoft; the SDK itself is free. @sickn33's azure-ai-ml-py skill: a hands-on reference for the Azure Machine Learning SDK v2 in Python β install azure-ai-ml, authenticate MLClient with DefaultAzureCredential (subscription ID, resource group, workspace name via environment variables or a config file), create and list workspaces, register data assets (files and folders), register and list models, create and scale compute clusters, submit and stream command jobs, build multi-step @dsl.pipeline workflows, create custom environments, and manage datastores β with an MLClient operations table, cost-conscious best practices (versioning, idle scale-down, tagging), and honest limitations (scope-bound, not a substitute for environment-specific validation). Honest caveats: the source frontmatter itself marks this skill "risk: critical" β sensible for anything that provisions cloud compute with your credentials; every job and cluster costs real money, so configure idle scale-down and keep an eye on quotas. MIT licensed (frontmatter and manifest agree). Skill Harbor never reviews the code, review it yourself before use. Discovered via skills.sh.
Version:
Install
Prerequisites: an Azure subscription (billed β compute, job runs, and storage cost real money), Python, and your Azure credentials (never hardcode them) Install "Azure AI/ML for Python β manage Azure ML workspaces, jobs, models, datasets, compute, pipelines" for me. It gives my agent @sickn33's Azure ML SDK v2 reference: install azure-ai-ml, authenticate MLClient via DefaultAzureCredential (subscription ID, resource group, workspace name from environment variables or a config file), create and list workspaces, register data assets and models, create and scale compute clusters with idle scale-down, submit and stream command jobs, build @dsl.pipeline multi-step workflows, create custom environments, and manage datastores β following the cost-conscious best practices (versioning, idle scale-down, tagging). MIT licensed. Repository: https://github.com/sickn33/agentic-awesome-skills/blob/main/plugins/agentic-awesome-skills-claude/skills/azure-ai-ml-py/SKILL.md 1. Fetch the SKILL.md file (and any helper files) from the repository path into a temporary folder and summarize what it does in one or two sentences. 2. Safety check: review the SKILL.md and scripts for anything suspicious (unexpected network calls, shell commands, credential harvesting). This repo should contain zero secrets in code, credentials only via environment variables, allowed hosts declared in the SKILL.md. Verify that holds here; STOP on any red flag and tell me. 3. Install it as a skill: copy SKILL.md and its helper files into the agent's skills directory, in a folder named "azure-ai-ml-py". 4. Verify with no network calls: frontmatter valid, files in place. 5. Report what was installed, where, and what I still need to do myself (e.g. set my Azure env vars in the vault, create the workspace, configure idle scale-down before submitting jobs). GitHub is optional: if I have a GitHub account or the gh CLI, you may use it; otherwise public access is fine. Never require it unless it's in the prerequisites above. Rules: don't touch anything outside the temp folder and the install target. If anything looks off, stop and ask me.
Questions
How do I install a build?
Every product page includes a copy-paste install prompt. Paste it into your Muse and it sets the build up for you β no manual configuration.
Where does my money go?
Straight to the seller. Skill Harbor never processes payments: checkout happens on the sellerβs own page, usually Stripe.
What does the β next to a creatorβs name mean?
It means we confirmed the identity of the person behind the listing. It says nothing about the code itself β always check a build before installing it.