Descubre Habilidades de Claude para data science & ml. Explora 53 habilidades y encuentra las capacidades perfectas para tus flujos de trabajo de IA.
Configures workspace environments to automatically prioritize established scientific research patterns, database access protocols, and package usage guidelines.
Implements comprehensive machine learning workflows including classification, regression, and data preprocessing using the industry-standard Scikit-learn library.
Optimizes data processing workflows using the high-performance Polars DataFrame library and expression API.
Queries and interprets NCBI ClinVar data to evaluate human genetic variants and their clinical significance.
Implements advanced prompting strategies like Chain-of-Thought and few-shot learning to optimize LLM performance and output reliability.
Facilitates direct access to PubMed literature and the NCBI E-utilities API for advanced biomedical research and data extraction.
Simplifies the development and training of Graph Neural Networks (GNNs) for deep learning on irregular and relational data structures.
Migrates legacy Python 2 scientific computing code to Python 3 using modern libraries like pandas, numpy, and pathlib.
Provides structured guidance for video analysis, motion detection, and temporal event tracking using computer vision techniques.
Optimizes semantic similarity retrieval tasks through expert guidance on document preprocessing, embedding model selection, and similarity ranking.
Translates Stan statistical models and inference code from R (RStan) to Python (PyStan 3.x) while handling API mappings and output differences.
Generates publication-quality scientific figures and multi-panel layouts compliant with major journal standards.
Reads, writes, and manipulates DICOM medical imaging data, including pixel arrays, metadata extraction, and file anonymization.
Builds and deploys machine learning models for complex time series tasks like forecasting, classification, and anomaly detection.
Integrates state-of-the-art machine learning models for NLP, computer vision, and audio tasks using the Hugging Face ecosystem.
Accesses the European Nucleotide Archive to retrieve genomic sequences, raw reads, and metadata for bioinformatics pipelines.
Applies medicinal chemistry rules and structural alerts to triage and prioritize compound libraries for drug discovery workflows.
Implements advanced multi-objective and many-objective optimization frameworks using state-of-the-art evolutionary algorithms and Pareto analysis.
Performs comprehensive hypothesis testing, regression analysis, and Bayesian statistics with automated assumption checking and APA-style reporting.
Queries and retrieves genomic data from NCBI Gene databases using E-utilities and the modern Datasets API.
Generates testable, evidence-based scientific hypotheses and experimental designs from observations or literature.
Accesses the world's largest somatic mutation database for cancer research and precision oncology data retrieval.
Implements minimal GPT-2 inference and transformer architectures within strict code size constraints.
Evaluates scientific rigor by assessing research methodology, statistical validity, and potential biases using industry-standard frameworks.
Designs and optimizes multi-component fusion protein sequences for FRET biosensors and gene synthesis.
Accesses the ZINC database of 230M+ purchasable compounds for drug discovery, virtual screening, and molecular analog searching.
Automates complex Excel data processing, visualization, and formatting using powerful Python libraries like Pandas and OpenPyXL.
Provides specialized guidance for implementing efficient Adaptive Rejection Sampling algorithms for log-concave probability distributions.
Generates high-quality visual content from text descriptions and image references using the Gemini API.
Applies Dead Simple Ontology Design Patterns to ensure consistency in term creation, naming conventions, and logical definitions.
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