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HappymathLabs
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happymath-skill

Perform AutoML, MCDM, differential equation, and optimization computations with Python.

7|1|Updated Nov 12, 2025
Search Tags:#machine learning#differential equations#mathematical optimization#automated machine learning#multi-criteria decision-making
One-click install
npx skills add https://github.com/HappymathLabs/happymath --skill happymath-skill
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: happymath-skill
Source: https://github.com/HappymathLabs/happymath/tree/main/skills/happymath_skill
Command: npx skills add https://github.com/HappymathLabs/happymath --skill happymath-skill

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires happymath, and includes scripts (resource) and references (resource) and assets (resource) components.

What problem does it solve?

This Skill simplifies complex mathematical computing and machine learning tasks with a focus on advanced analytics.

Core Features & Use Cases

  • AutoML: Automates machine learning for classification, regression, clustering, and time series analysis.
  • Decision: Offers comprehensive MCDM with over 80 algorithms for multi-criteria decision-making.
  • Differential Equations: Solves both ODEs and PDEs with a variety of numerical and symbolic methods.
  • Optimization: Provides a comprehensive framework for mathematical optimization.
  • Use Case: If you're dealing with a complex data set requiring classification, multi-criteria analysis, solving differential equations, or optimization, this skill is invaluable.

Quick Start

Run the AutoML feature on a given dataset using 'happymath.AutoML.fit'.

Frequently Asked Questions about happymath-skill

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I automate machine learning for classification and regression tasks?▼

To automate machine learning, use the AutoML feature to run model fitting for classification, regression, clustering, and time series analysis on your dataset. It streamlines the modeling process for advanced analytics.

What is multi-criteria decision-making and how many algorithms are available?▼

Multi-criteria decision-making evaluates multiple conflicting criteria in decision-making, and this Skill provides over 80 algorithms to handle complex MCDM tasks for comprehensive data analysis.

How do I solve differential equations using Python and SciPy?▼

You can solve differential equations by applying the Skill's numerical and symbolic methods to handle both ordinary and partial differential equations using Python, NumPy, and SciPy.

Do I need NumPy and SciPy installed to run mathematical optimization tasks?▼

Yes, NumPy and SciPy are required dependencies. You must have these Python libraries installed in your environment to execute mathematical optimization and advanced modeling computations.

What's the best way to start automated machine learning on a dataset?▼

The best way to start automated machine learning is to run the fit function on your target dataset, which initializes the AutoML process for classification, regression, clustering, or time series analysis.

Are there limitations when using automated machine learning for time series analysis?▼

The Skill handles time series analysis within its automated machine learning framework, but successful results depend on dataset quality and the underlying NumPy and SciPy computational limits.

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