skills/domains/ai-ml/SKILL.md
27 ai & machine learning skills. Trigger: ML experiments, model training, deep learning, NLP, computer vision. Design: covers frameworks, benchmarks, paper reproduction, and AI research workflows.
npx skillsauth add wentorai/research-plugins ai-ml-skillsInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
3 of 9 scanners reported clean
Some scanners were skipped, did not run, or reported a non-clean status. Review each row below.
Select the skill matching the user's need, then read its SKILL.md.
| Skill | Description | |-------|-------------| | ai-agent-papers-guide | Curated 2024-2026 AI agent research papers collection | | ai-model-benchmarking | Benchmark AI models across 60+ academic evaluation suites and metrics | | anomaly-detection-papers-guide | Industrial anomaly detection methods and benchmark papers | | autonomous-agents-papers-guide | Daily-updated collection of autonomous AI agent papers | | computer-vision-guide | Apply computer vision research methods, models, and evaluation tools | | deep-learning-papers-guide | Annotated deep learning paper implementations with code walkthroughs | | dl-transformer-finetune | Build transformer fine-tuning plans for classification and generation | | domain-adaptation-papers-guide | Comprehensive collection of domain adaptation research papers | | generative-ai-guide | Curated guide to generative AI covering LLMs and diffusion models | | graph-learning-papers-guide | Conference papers on graph neural networks and graph learning | | huggingface-api | Search and discover ML models, datasets, and Spaces on Hugging Face | | huggingface-inference-guide | Run NLP and CV model inference via Hugging Face free-tier API | | keras-deep-learning | Build and debug deep learning models with Keras and TensorFlow backend | | kolmogorov-arnold-networks-guide | Papers and tutorials on KAN learnable activation networks | | llm-evaluation-guide | Evaluate and benchmark large language models for research applications | | llm-from-scratch-guide | Build a ChatGPT-like LLM from scratch using PyTorch step by step | | ml-pipeline-guide | Build and deploy reproducible production ML pipelines for research | | nlp-toolkit-guide | NLP analysis with perplexity scoring, burstiness, and entropy metrics | | npcpy-research-guide | All-in-one Python library for NLP, agents, and knowledge graphs | | prompt-engineering-research | Systematic prompt engineering methods for AI-assisted academic research workf... | | pytorch-guide | Avoid common PyTorch mistakes and apply robust training patterns | | pytorch-lightning-guide | PyTorch Lightning framework for scalable model training and research | | reinforcement-learning-guide | Reinforcement learning fundamentals, algorithms, and research | | responsible-ai-guide | Resources for trustworthy, fair, and ethical AI research | | tensorflow-guide | TensorFlow best practices for tf.function, GPU memory, and deployment | | transformer-architecture-guide | Guide to Transformer architectures for NLP and computer vision | | vmas-simulator-guide | Vectorized multi-agent reinforcement learning simulator |
tools
10 document processing skills. Trigger: extracting text from PDFs, parsing references, document Q&A. Design: parsing pipelines (GROBID, marker) and structured extraction tools.
documentation
Guide to tldraw for infinite canvas whiteboarding and diagram creation
testing
Create graphical abstracts, schematic diagrams, and scientific illustrations
documentation
Create UML diagrams and architecture visualizations with PlantUML