Discover Agent Skills for data science & ml. Browse 61skills for Claude, ChatGPT & Codex.
Implements high-performance persistent memory and pattern learning for stateful AI agents using AgentDB.
Automates the adaptation and fine-tuning of pre-trained machine learning models for specific tasks and new datasets.
Deploys and trains autonomous agents using nine reinforcement learning algorithms integrated with the AgentDB ecosystem.
Queries the NCBI ClinVar database to identify genetic variants, interpret pathogenicity classifications, and annotate genomic data for bioinformatics pipelines.
Automates the creation of end-to-end machine learning pipelines including data validation, model selection, and hyperparameter tuning.
Automates the design, configuration, and implementation of complex neural network architectures through natural language commands.
Provides direct REST API access to the UniProt database for protein search, sequence retrieval, and cross-database ID mapping.
Accesses the comprehensive BRENDA enzyme database to retrieve kinetic parameters, reaction equations, and biochemical data via SOAP API.
Implements high-performance semantic vector search and HNSW indexing for intelligent document retrieval and RAG systems.
Queries the Dimensions database to find and analyze academic publications, grants, patents, and clinical trials for evidence-based research.
Facilitates creative research ideation by generating hypotheses, identifying research gaps, and exploring interdisciplinary connections.
Conducts systematic, multi-database academic literature reviews with verified citations and professional formatting.
Generates publication-quality, journal-ready figures and multi-panel scientific visualizations following academic standards.
Facilitates creative research ideation and exploratory scientific problem-solving through interdisciplinary analogies and assumption-challenging frameworks.
Implements reliable, reproducible data pipelines and infrastructure using best practices for ETL/ELT workflows.
Integrates real-time account performance metrics and drawdown penalties into Reinforcement Learning models to optimize trading risk management.
Simulates and analyzes open and closed quantum systems using the Quantum Toolbox in Python.
Optimizes Claude Code interactions with the GLM-4.7 model through advanced prompting patterns and multi-agent ensemble strategies.
Manages FiftyOne dataset visualization and curation workflows using Podman Quadlet containers with MongoDB persistence.
Optimizes Large Language Model fine-tuning through advanced QLoRA experimentation patterns, rank selection, and adapter management.
Enables seamless integration between Ollama and the OpenAI ecosystem using a compatible API layer for popular libraries.
Accelerates LLM inference by up to 2x using Unsloth and vLLM backends for optimized model execution.
Manages LocalAI inference services with GPU acceleration using Podman Quadlet containers for local model hosting.
Imports GGUF models directly from HuggingFace into Ollama for immediate local inference and testing.
Implements Retrieval-Augmented Generation workflows to ground AI responses with external knowledge and private documents.
Manages and configures Open WebUI instances for interacting with Ollama models via Podman containers.
Manages multiple JupyterLab development environments with GPU acceleration using Podman Quadlet containers.
Provides expert guidance and implementation patterns for fine-tuning Large Language Models using PyTorch and HuggingFace.
Optimizes LLM alignment through Group Relative Policy Optimization (GRPO) for stable reinforcement learning and reasoning model training.
Fine-tunes and optimizes vision-language models like Pixtral and Ministral using Unsloth's FastVisionModel and LoRA.
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