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neural-network-builder

Build and configure neural network architectures

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■ INSTALL // npx @self.md/cli install neural-network-builder
AuthorJeremy Longshore
Namespace@jeremylongshore/claude-code-plugins-plus
Category#ai-ml
Version1.0.0
Stars★ 1,193
Downloads↓ 3
Verification[ ✓ ] self.md verified

Build and configure neural network architectures

Installation

npx claude-plugins install @jeremylongshore/claude-code-plugins-plus/neural-network-builder

Contents

Folders: commands, skills

Files: LICENSE, README.md

Documentation

Build and configure neural network architectures

Installation

/plugin install neural-network-builder@claude-code-plugins-plus

Usage

/build-nn

Features

  • Automated workflows
  • Best practices implementation
  • Performance optimization
  • Error handling

Requirements

  • Python 3.8+
  • Standard ML libraries

License

MIT

Included Skills

This plugin includes 1 skill definition:

building-neural-networks

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View skill definition

Neural Network Builder

This skill provides automated assistance for neural network builder tasks.

Overview

This skill empowers Claude to design and implement neural networks tailored to specific tasks. It leverages the neural-network-builder plugin to automate the process of defining network architectures, configuring layers, and setting training parameters. This ensures efficient and accurate creation of neural network models.

How It Works

  1. Analyzing Requirements: Claude analyzes the user’s request to understand the desired neural network architecture, task, and performance goals.
  2. Generating Configuration: Based on the analysis, Claude generates the appropriate configuration for the neural-network-builder plugin, specifying the layers, activation functions, and other relevant parameters.
  3. Executing Build: Claude executes the build-nn command, triggering the neural-network-builder plugin to construct the neural network based on the generated configuration.

When to Use This Skill

This skill activates when you need to:

  • Create a new neural network architecture for a specific machine learning task.
  • Modify an existing neural network’s layers, parameters, or training process.
  • Design a neural network using specific layer types, such as convolutional, recurrent, or transformer layers.

Examples

Example 1: Image Classification

User request: “Build a convolutional neural network for image classification with three convolutional laye

Source

View on GitHub