Building Recommendation Systems

This skill enables Claude to design and implement recommendation systems tailored to specific datasets and use cases. It automates the process of selecting appropriate algorithms, preprocessing data, training models, and evaluating performance, ultimately providing users with a functional recommendation engine.

Writing & Content Plugin marketplace

Install

Claude Code plugin
/plugin marketplace add jeremylongshore/claude-code-plugins-plus-skills
/plugin install recommendation-engine@claude-code-plugins-plus

Run these inside Claude Code. The skill comes with its plugin.

What this skill does

This skill empowers Claude to construct recommendation systems using collaborative filtering, content-based filtering, or hybrid approaches. It analyzes user preferences, item features, and interaction data to generate personalized recommendations. Use this skill when the user requests to build a recommendation engine, needs help with collaborative filtering, wants to implement content-based filtering, or seeks to rank items based on relevance for a specific user or group of users. It is triggered by requests involving "recommendations", "collaborative filtering", "content-based filtering", "r

Trigger phrases

Claude loads this skill automatically when you say things like:

“recommendations”“collaborative filtering”“content-based filtering”“ranking items”“building a recommender”

How it works

  1. Generating Code: Claude generates Python code using relevant libraries (e.g., scikit-learn, TensorFlow, PyTorch) to build the recommendation model. This includes data loading, preprocessing, model training, and evaluation.
  2. Implementing Best Practices: The code incorporates best practices for recommendation system development, such as handling cold starts, addressing scalability, and mitigating bias.

When to use it

  • Build a personalized movie recommendation system.
  • Create a product recommendation engine for an e-commerce platform.
  • Implement a content recommendation system for a news website.

Best practices

  • Model Evaluation: Use appropriate metrics (e.g., precision, recall, NDCG) to evaluate the performance of the recommendation system.
  • Scalability: Design the recommendation system to handle large datasets and user bases efficiently.

Details

Skill name
building-recommendation-systems
Repository
jeremylongshore/claude-code-plugins-plus-skills
Plugin
recommendation-engine

FAQ

What does the Building Recommendation Systems skill do?

This skill empowers Claude to construct recommendation systems using collaborative filtering, content-based filtering, or hybrid approaches. It analyzes user preferences, item features, and interaction data to generate personalized recommendations. Use this skill when the user requests to build a recommendation engine, needs help with collaborative filtering, wants to implement content-based filtering, or seeks to rank items based on relevance for a specific user or group of users. It is triggered by requests involving "recommendations", "collaborative filtering", "content-based filtering", "r

How do I install the Building Recommendation Systems skill?

Claude Code plugin: /plugin marketplace add jeremylongshore/claude-code-plugins-plus-skills then /plugin install recommendation-engine@claude-code-plugins-plus. Skills go in ~/.claude/skills (personal) or .claude/skills (project), and Claude loads them automatically when a task matches the description.

Related skills

000 Jeremy Content Consistency Validator

jeremylongshore/claude-code-plugins-plus-skills

Validates messaging consistency across website, GitHub repositories, and local documentation. Generates comprehensive read-only discrepancy reports showing where messaging conflicts or inconsistencies exist. Activates when user mentions "consistency check", "validate documentation", "check for mixed messaging", "audit content consistency", or before updating internal paperwork.

Writing & Content

001 Jeremy Taskwarrior Integration

jeremylongshore/claude-code-plugins-plus-skills

Enforces complete Taskwarrior integration protocol for ALL coding tasks. Activates automatically when user mentions "taskwarrior", "task warrior", "tw", or discusses task management. Decomposes all coding work into properly tracked Taskwarrior tasks with full lifecycle: task add → task start → implementation → task done. Integrates with Timewarrior for automatic time tracking.

Productivity & Notes

Adapting Transfer Learning Models

jeremylongshore/claude-code-plugins-plus-skills

This skill automates the adaptation of pre-trained machine learning models using transfer learning techniques. It is triggered when the user requests assistance with fine-tuning a model, adapting a pre-trained model to a new dataset, or performing transfer learning. It analyzes the user's requirements, generates code for adapting the model, includes data validation and error handling, provides performance metrics, and saves artifacts with documentation. Use this skill when you need to leverage existing models for new tasks or datasets, optimizing for performance and efficiency.

Learning & Education

Duckdb Docs

duckdb/duckdb-skills

Search DuckDB and DuckLake documentation and blog posts. Returns relevant doc chunks for a question or keyword using full-text search against a locally cached index.

Writing & ContentIn 1 list

Skill Seekers

Converts documentation websites into Claude Skills. Transform existing documentation into structured skills for Claude.

Writing & Content

Diasporic Intelligence

MinistaJazz/diasporic-intelligence

Use when writing, reviewing, citing, or implementing Diasporic Intelligence, a source-credited framework also described as Afrotemporalism in Action. Preserves source credit, consent governance, provenance, revocation, lineage boundaries, and the distinction from generic cultural AI, biometric extraction, and ancestor impersonation.

Writing & ContentIn 1 list

Browse the most popular Claude skills, all writing & content skills, or write your own with the skills generator.