gradient-methods

Community

Optimize with gradient-based methods.

Authorparcadei
Version1.0.0
Installs0

System Documentation

What problem does it solve?

This Skill provides strategies and tools for solving optimization problems using gradient-based methods, helping users find optimal solutions efficiently.

Core Features & Use Cases

  • Gradient Descent Variants: Implements basic and accelerated gradient descent methods.
  • Step Size Selection: Offers guidance on choosing appropriate step sizes (fixed, backtracking, adaptive).
  • Newton's Method: Includes information on Newton's method and its quasi-Newton approximations.
  • Use Case: When facing a complex function minimization task, this skill can guide you through selecting the right algorithm and parameters for faster convergence.

Quick Start

Use the gradient-methods skill to find the minimum of the function x^2 + y^2 using the CG method.

Dependency Matrix

Required Modules

scipysympy

Components

scriptsreferences

💻 Claude Code Installation

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Please help me install this Skill:
Name: gradient-methods
Download link: https://github.com/parcadei/Continuous-Claude-v3/archive/main.zip#gradient-methods

Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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