ai-ml-skills

---
name: ai-ml-skills
description: "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."
---

# AI & Machine Learning — 27 Skills

Select the skill matching the user's need, then `read` its SKILL.md.

| Skill | Description |
|-------|-------------|
| [ai-agent-papers-guide](./ai-agent-papers-guide/SKILL.md) | Curated 2024-2026 AI agent research papers collection |
| [ai-model-benchmarking](./ai-model-benchmarking/SKILL.md) | Benchmark AI models across 60+ academic evaluation suites and metrics |
| [anomaly-detection-papers-guide](./anomaly-detection-papers-guide/SKILL.md) | Industrial anomaly detection methods and benchmark papers |
| [autonomous-agents-papers-guide](./autonomous-agents-papers-guide/SKILL.md) | Daily-updated collection of autonomous AI agent papers |
| [computer-vision-guide](./computer-vision-guide/SKILL.md) | Apply computer vision research methods, models, and evaluation tools |
| [deep-learning-papers-guide](./deep-learning-papers-guide/SKILL.md) | Annotated deep learning paper implementations with code walkthroughs |
| [dl-transformer-finetune](./dl-transformer-finetune/SKILL.md) | Build transformer fine-tuning plans for classification and generation |
| [domain-adaptation-papers-guide](./domain-adaptation-papers-guide/SKILL.md) | Comprehensive collection of domain adaptation research papers |
| [generative-ai-guide](./generative-ai-guide/SKILL.md) | Curated guide to generative AI covering LLMs and diffusion models |
| [graph-learning-papers-guide](./graph-learning-papers-guide/SKILL.md) | Conference papers on graph neural networks and graph learning |
| [huggingface-api](./huggingface-api/SKILL.md) | Search and discover ML models, datasets, and Spaces on Hugging Face |
| [huggingface-inference-guide](./huggingface-inference-guide/SKILL.md) | Run NLP and CV model inference via Hugging Face free-tier API |
| [keras-deep-learning](./keras-deep-learning/SKILL.md) | Build and debug deep learning models with Keras and TensorFlow backend |
| [kolmogorov-arnold-networks-guide](./kolmogorov-arnold-networks-guide/SKILL.md) | Papers and tutorials on KAN learnable activation networks |
| [llm-evaluation-guide](./llm-evaluation-guide/SKILL.md) | Evaluate and benchmark large language models for research applications |
| [llm-from-scratch-guide](./llm-from-scratch-guide/SKILL.md) | Build a ChatGPT-like LLM from scratch using PyTorch step by step |
| [ml-pipeline-guide](./ml-pipeline-guide/SKILL.md) | Build and deploy reproducible production ML pipelines for research |
| [nlp-toolkit-guide](./nlp-toolkit-guide/SKILL.md) | NLP analysis with perplexity scoring, burstiness, and entropy metrics |
| [npcpy-research-guide](./npcpy-research-guide/SKILL.md) | All-in-one Python library for NLP, agents, and knowledge graphs |
| [prompt-engineering-research](./prompt-engineering-research/SKILL.md) | Systematic prompt engineering methods for AI-assisted academic research workf... |
| [pytorch-guide](./pytorch-guide/SKILL.md) | Avoid common PyTorch mistakes and apply robust training patterns |
| [pytorch-lightning-guide](./pytorch-lightning-guide/SKILL.md) | PyTorch Lightning framework for scalable model training and research |
| [reinforcement-learning-guide](./reinforcement-learning-guide/SKILL.md) | Reinforcement learning fundamentals, algorithms, and research |
| [responsible-ai-guide](./responsible-ai-guide/SKILL.md) | Resources for trustworthy, fair, and ethical AI research |
| [tensorflow-guide](./tensorflow-guide/SKILL.md) | TensorFlow best practices for tf.function, GPU memory, and deployment |
| [transformer-architecture-guide](./transformer-architecture-guide/SKILL.md) | Guide to Transformer architectures for NLP and computer vision |
| [vmas-simulator-guide](./vmas-simulator-guide/SKILL.md) | Vectorized multi-agent reinforcement learning simulator |