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	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