发现data science & ml类别的 Claude 技能。浏览 61 个技能,找到适合您 AI 工作流程的完美功能。
Develops, backtests, and optimizes systematic trading strategies with integrated risk management and bias detection.
Performs comprehensive exploratory data analysis on over 200 scientific file formats to generate detailed quality reports and statistical summaries.
Retrieves and analyzes protein-protein interaction networks and functional enrichment data directly from the STRING database.
Generates professional data visualizations, charts, and graphs from raw datasets to uncover patterns and insights automatically.
Transforms raw datasets into informative and visually compelling charts, plots, and graphs using intelligent automated selection.
Executes real-time, AI-powered web searches with cited sources and scientific literature access using Perplexity models.
Queries the Open Targets Platform to identify and prioritize therapeutic drug targets through genetic, omics, and clinical evidence.
Accesses and analyzes over 200 million AI-predicted protein structures for drug discovery and structural biology research.
Performs comprehensive statistical testing, hypothesis verification, and APA-compliant reporting for academic and scientific research.
Builds scalable, production-grade data pipelines and ETL/ELT systems using the modern data stack.
Streamlines the creation of visually engaging, research-backed scientific presentations for conferences, seminars, and academic defenses.
Accesses comprehensive pharmacogenomics data to query gene-drug interactions, CPIC guidelines, and genotype-guided dosing recommendations.
Automates the transition of machine learning models into production-ready environments and high-performance APIs.
Accesses UniProt's comprehensive protein sequence and functional information resource via REST API for bioinformatics workflows.
Queries ChEMBL's vast database of bioactive molecules and bioactivity data to accelerate medicinal chemistry and drug discovery research.
Formulates testable scientific hypotheses and experimental designs supported by literature synthesis and publication-quality schematics.
Models complex discrete-event systems using Python to analyze resource contention, queue behavior, and process efficiency.
Manages and tracks AI/ML model versions, performance metrics, and lineage directly within the Claude Code environment.
Architects and deploys production-grade computer vision systems including object detection, segmentation, and real-time video processing using state-of-the-art AI models.
Implements and optimizes reinforcement learning workflows using the PyTorch-based Stable Baselines3 library.
Builds machine learning models and unsupervised embeddings for genomic interval data and BED file collections.
Simulates complex fluid dynamics using high-performance Python pseudospectral methods and solvers for Navier-Stokes and geophysical flows.
Implements optimal document segmentation techniques to improve retrieval-augmented generation (RAG) performance and search accuracy.
Analyzes the emotional tone of text data to classify sentiment as positive, negative, or neutral for customer feedback and social media monitoring.
Generates publication-quality scientific figures and multi-panel plots adhering to journal standards and accessibility guidelines.
Enables advanced biomedical literature searches and programmatic data retrieval via the PubMed E-utilities REST API.
Implements comprehensive survival analysis and time-to-event modeling workflows using the scikit-survival library.
Builds, analyzes, and visualizes complex graph structures and network data using the powerful NetworkX Python library.
Builds declarative, type-safe AI services in Java using LangChain4j interfaces, annotations, and memory management.
Architects sophisticated LLM applications using LangChain's agents, memory systems, and complex chain integration patterns.
Scroll for more results...