data science & ml Claude 스킬을 발견하세요. 61개의 스킬을 탐색하고 AI 워크플로우에 완벽한 기능을 찾아보세요.
Facilitates drug discovery and therapeutic machine learning by providing AI-ready datasets, benchmarks, and molecular evaluation oracles.
Architects sophisticated LLM applications using LangChain's agents, memory systems, and complex chain integration patterns.
Builds declarative, type-safe AI services in Java using LangChain4j interfaces, annotations, and memory management.
Implements comprehensive survival analysis and time-to-event modeling workflows using the scikit-survival library.
Enables advanced biomedical literature searches and programmatic data retrieval via the PubMed E-utilities REST API.
Generates publication-quality scientific figures and multi-panel plots adhering to journal standards and accessibility guidelines.
Implements optimal document segmentation techniques to improve retrieval-augmented generation (RAG) performance and search accuracy.
Simulates complex fluid dynamics using high-performance Python pseudospectral methods and solvers for Navier-Stokes and geophysical flows.
Builds machine learning models and unsupervised embeddings for genomic interval data and BED file collections.
Implements and optimizes reinforcement learning workflows using the PyTorch-based Stable Baselines3 library.
Architects and deploys production-grade computer vision systems including object detection, segmentation, and real-time video processing using state-of-the-art AI models.
Models complex discrete-event systems using Python to analyze resource contention, queue behavior, and process efficiency.
Formulates testable scientific hypotheses and experimental designs supported by literature synthesis and publication-quality schematics.
Queries ChEMBL's vast database of bioactive molecules and bioactivity data to accelerate medicinal chemistry and drug discovery research.
Accesses UniProt's comprehensive protein sequence and functional information resource via REST API for bioinformatics workflows.
Accesses comprehensive pharmacogenomics data to query gene-drug interactions, CPIC guidelines, and genotype-guided dosing recommendations.
Streamlines the creation of visually engaging, research-backed scientific presentations for conferences, seminars, and academic defenses.
Builds scalable, production-grade data pipelines and ETL/ELT systems using the modern data stack.
Performs comprehensive statistical testing, hypothesis verification, and APA-compliant reporting for academic and scientific research.
Accesses and analyzes over 200 million AI-predicted protein structures for drug discovery and structural biology research.
Queries the Open Targets Platform to identify and prioritize therapeutic drug targets through genetic, omics, and clinical evidence.
Executes real-time, AI-powered web searches with cited sources and scientific literature access using Perplexity models.
Retrieves and analyzes protein-protein interaction networks and functional enrichment data directly from the STRING database.
Performs comprehensive exploratory data analysis on over 200 scientific file formats to generate detailed quality reports and statistical summaries.
Analyzes logistics exports to provide structured rate preparation intelligence and shipping profile discovery.
Develops, backtests, and optimizes systematic trading strategies with integrated risk management and bias detection.
Retrieves real-time quotes, historical OHLCV data, and comprehensive option chains from 25+ Indian brokers using the OpenAlgo Python SDK.
Automates the analysis, manipulation, and visualization of Excel spreadsheets using Python-based data science libraries.
Analyzes shipping export data to identify cost-saving opportunities and FirstMile logistics network compatibility.
Guides the architectural design and refactoring of AI agents into focused, single-purpose specialists to maximize performance and accuracy.
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