发现data science & ml类别的 Claude 技能。浏览 53 个技能,找到适合您 AI 工作流程的完美功能。
Performs hydrological modeling and streamflow forecasting using Julia-based classical and machine learning models.
Analyzes LangGraph application workflows to identify performance bottlenecks and propose architecture-level optimizations for cost, latency, and accuracy.
Processes, analyzes, and generates audio, video, image, and document content using Google Gemini's powerful multimodal API.
Automates the creation, configuration, and deployment of machine learning demos on Hugging Face Spaces using Gradio, Streamlit, and ZeroGPU.
Optimizes LangGraph application performance through iterative prompt engineering and node-level logic refinements based on quantitative evaluation criteria.
Predicts high-accuracy 3D protein-ligand binding poses using diffusion-based deep learning for structure-based drug design.
Performs high-performance nonlinear dimensionality reduction for data visualization, clustering preprocessing, and supervised manifold learning.
Manipulates genomic datasets and processes Next-Generation Sequencing (NGS) files using a Pythonic interface to htslib.
Optimizes AI agent performance through Anthropic-based context engineering and prompt structure standards.
Provides comprehensive tools for astronomical data analysis, coordinate transformations, and cosmological calculations within Python environments.
Analyzes biological data including sequences, phylogenetic trees, and microbial diversity metrics using specialized Python tools.
Empowers AI agents to learn and improve through experience using 9 specialized reinforcement learning algorithms and WASM-accelerated inference.
Enables high-performance distributed vector search and multi-agent coordination using QUIC synchronization and hybrid search.
Simulates and analyzes quantum mechanical systems using the Quantum Toolbox in Python (QuTiP).
Implements adaptive learning and meta-cognitive systems to enable AI agents to recognize patterns and optimize strategies through experience.
Accesses and manages AI-ready drug discovery datasets, benchmarks, and molecular oracles for therapeutic machine learning.
Processes and prepares whole slide pathology images for deep learning and digital pathology workflows.
Optimizes 5G RAN mobility and handover performance using cognitive AI and predictive trajectory modeling.
Implements high-performance persistent memory and pattern learning for stateful AI agents using AgentDB.
Executes high-performance computational fluid dynamics simulations and analysis using pseudospectral methods in Python.
Enables advanced geospatial vector data analysis, geometric operations, and spatial mapping within Python environments.
Streamlines computational molecular biology tasks and bioinformatics workflows using the Biopython library.
Conducts advanced machine learning research for Radio Access Networks using reinforcement learning, causal inference, and cognitive frameworks.
Manages annotated data matrices and metadata for single-cell genomics and large-scale biological datasets in Python.
Streamlines scientific development on HPC environments using multi-root workspaces and automated test data extraction.
Manages and routes requests across multiple AI providers including Anthropic, Ollama, and HuggingFace.
Streamlines the development of AI-powered features within the Moodle LMS using the official AI Subsystem for version 4.5 and above.
Prevents Jupyter notebook hangs by explicitly managing CuPy GPU memory pools and Python garbage collection.
Implements and manages Retrieval-Augmented Generation (RAG) systems using Weaviate vector databases for semantic search and document retrieval.
Optimizes Python codebases using verified, low-risk patterns for I/O, NumPy operations, and efficient directory scanning.
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