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Ml Model Training

Checked
aj-geddes·vlatest·ai-ml·MIT

Helps with machine learning, data modeling as part of agent workflows workflows.

Repository

Install on your platform

Showing Claude Code. One command installs this skill into any of the agents below.

Installs under a different name. Its SKILL.md names it ML Model Training, not the name it is listed under, so the command below uses that name.
  1. 1

    Run this in your project

    terminal
    $ npx skills add aj-geddes/useful-ai-prompts --skill "ML Model Training" -a claude-code

  2. Uses the open-source skills CLI and needs Node.js. Add -g to install it for your user instead of this project.

What we know about this skill

Publisher

aj-geddes

Taken from the source listing. We haven't verified who controls this account.

Install target

Live repository

Not pinned. Installing fetches whatever the repository holds at the time you run the command.

No human has reviewed this code. The checks below are a static scan of the files at one commit — nobody has run this skill or judged whether it works. A skill runs with whatever access you give your agent, so read the source before you install it.

Automated safety checks

scanned

This skill passed all 6 checks. We read its files at one commit and looked for the things that make a skill dangerous to run — not for whether it works.

  • Declares what it does: passed

    SKILL.md parses and declares a name and a description.

    SKILL.md exists, its frontmatter parses, and it declares a name and a description.

  • No undeclared network calls: passed

    Makes no network calls.

    Every host the skill dials — from its scripts, its config endpoints or the commands it tells the agent to run — is either well-known package and API infrastructure or declared in its own frontmatter. Links in documentation are not counted.

  • No obfuscated payloads: passed

    No encoded or obfuscated payloads.

    No base64, hex or compressed blob is decoded and then executed, and no encoded shell commands.

  • No credential access: passed

    Reads no keys, tokens, keychains or credential files.

    Neither the code nor the SKILL.md instructions read SSH keys, cloud credentials, keychains, token stores, browser cookie databases or dotfiles that hold secrets.

  • No pipe-to-shell installers: passed

    No pipe-to-shell or download-and-run installers.

    No `curl … | sh` pattern, in the code or in the instructions, that runs code fetched at run time.

  • Pinned to a commit: passed

    Scanned aj-geddes/useful-ai-prompts at 3f5182cfd7.

    The exact upstream commit SHA that was scanned is recorded, so the result refers to specific bytes.

Commit
3f5182cfd7
Manifest
skills/ml-model-training/SKILL.md
Scanned
3 files, 289 lines
This is a static scan, not a review. It reads the skill's files; it does not run them, and it cannot tell you whether the skill is any good or whether the code does what its description says. A skill runs with whatever access you give your agent.
What each check looks for →

About this skill

ML Model Training

What it does

This skill enables AI agents to execute machine learning model training workflows, allowing them to process datasets and generate predictive models autonomously. It bridges the gap between raw data and actionable insights by automating the core computational steps of model development.

When to use it

  • Automated Forecasting: Generate time-series predictions for inventory levels or sales trends without manual coding.
  • Pattern Recognition: Train classifiers to identify specific anomalies within large volumes of unstructured logs or images.
  • Rapid Prototyping: Quickly test multiple algorithm configurations on a new dataset to find the best fit before deployment.
  • Custom Solution Development: Build specialized models tailored to niche business requirements that lack off-the-shelf solutions.

Key capabilities

  • Executes end-to-end training pipelines for machine learning algorithms.
  • Processes and prepares raw datasets for model ingestion.
  • Generates trained model artifacts ready for integration into other agent workflows.
  • Supports various model types suitable for regression, classification, and clustering tasks.

Example prompts

  • "Train a logistic regression model on this customer churn dataset to predict future attrition rates."
  • "Run a training job on the provided image set to classify objects as either 'safe' or 'hazardous'."
  • "Develop a linear regression model using historical sales data to forecast next quarter's revenue."

Tips & gotchas

Ensure your input datasets are cleaned and formatted correctly before initiating training, as poor data quality directly impacts model accuracy. Be aware that this skill requires access to computational resources; very large datasets may need preprocessing or splitting to run efficiently within the agent's environment.