nlp-processing
Process and analyze natural language using modern NLP techniques. Use for text classification, named entity recognition, sentiment analysis, tokenization, embeddings, transformers (BERT, GPT), and language understanding tasks.
npx skills add majiayu000/claude-skill-registry --skill nlp-processing --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# NLP Processing Process and analyze natural language using modern techniques and transformer models. ## Overview Natural Language Processing enables computers to understand, interpret, and generate human language. This skill covers fundamental techniques through state-of-the-art transformer models. ## Quick Reference | Scenario | Recommended Approach | Reference File | |----------|---------------------|----------------| | Text preprocessing and tokenization | Cleaning, normalization, tokenization | `/references/preprocessing.md` | | Text classification and sentiment analysis | Fine-tuned transformers or classical ML | `/references/classification.md` | | Named entities, POS tagging, parsing | Sequence labeling with transformers | `/references/sequence-labeling.md` | | Embeddings and semantic similarity | Sentence transformers, BERT embeddings | `/references/embeddings.md` | ## Core Principles 1. **Tokenization** - Split text into meaningful units 2. **Representation** - Convert text to numerical vectors 3. **Context** - Capture word meaning from surrounding words 4. **Transfer Learning** - Leverage pre-trained models 5. **Fine-Tuning** - Adapt models to specific tasks ## NLP Pipeli
- Overview
- Quick Reference
- Core Principles
- NLP Pipeline
- 1. Preprocessing
- 2. Representation
- 3. Modeling
- 4. Post-processing
- Key Tasks
- Using the Reference Files
- Best Practices
- Common Pitfalls to Avoid
What does the nlp-processing skill do?
Process and analyze natural language using modern NLP techniques. Use for text classification, named entity recognition, sentiment analysis, tokenization, embeddings, transformers (BERT, GPT), and language understanding tasks.
How do I install it?
Run `npx skills add majiayu000/claude-skill-registry --skill nlp-processing --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From majiayu000/claude-skill-registry, a repository with 534 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.