Total 50,676 skills, AI & Machine Learning has 8495 skills
Showing 12 of 8495 skills
Expert in Barcelona's transportation geography (El Prat Airport, Sants Station) and taxi sector operational patterns.
Open-source AI observability platform for LLM tracing, evaluation, and monitoring. Use when debugging LLM applications with detailed traces, running evaluations on datasets, or monitoring production AI systems with real-time insights.
Expert guidance for fine-tuning LLMs with Axolotl - YAML configs, 100+ models, LoRA/QLoRA, DPO/KTO/ORPO/GRPO, multimodal support
Use when you need legal PDF to markdown extraction plus clause chunking and embedding prep; pair with addon-rag-ingestion-pipeline and architect-python-uv-batch.
Bridge web search capability for LLM workflows. Use when user asks for latest info, external facts, or source links and the active model/toolchain lacks direct search ability.
Detectar sobreexposición, subexposición e iluminación desigual en frames capturados
Write, audit, and improve agent context files (AGENTS.md, CLAUDE.md) for AI coding agents. Use when creating or improving agent context for a codebase.
Sklearn Pipeline Builder - Auto-activating skill for ML Training. Triggers on: sklearn pipeline builder, sklearn pipeline builder Part of the ML Training skill category.
Terminal-Bench integration for Mux agent benchmarking and failure analysis
Unified YouTube script creation for cardiology channels in Hinglish. Uses the COMPLETE research-engine pipeline (channel scraping, comment analysis, narrative monitoring, gap finding, view prediction) combined with RAG + PubMed for evidence. Data-driven topic selection, 15-30 min educational videos with 6-point voice check.
Generate videos from text and image prompts via Together AI. 15+ models including Veo 2/3, Sora 2, Kling 2.1, Hailuo 02, Seedance, PixVerse, Vidu. Supports text-to-video, image-to-video, keyframe control, and reference images. Use when users want to generate videos, create video content, animate images, or work with any video generation task.
Guidelines for deep learning development with PyTorch, Transformers, Diffusers, and Gradio for LLM and diffusion model work.