data science & ml Claude 스킬을 발견하세요. 61개의 스킬을 탐색하고 AI 워크플로우에 완벽한 기능을 찾아보세요.
Automates professional spreadsheet creation, data analysis, and financial modeling with rigorous formula validation.
Safely removes intermediate files and temporary data from completed research sessions while preserving critical findings and source papers.
Automates advanced spreadsheet creation, data analysis, and professional financial modeling with rigorous formula validation.
Evaluates machine learning model performance using a comprehensive suite of metrics to ensure accuracy and deployment readiness.
Designs and implements personalized recommendation systems using collaborative filtering, content-based models, and hybrid approaches.
Builds, optimizes, and evaluates robust supervised machine learning classification models automatically from labeled datasets.
Builds and evaluates robust supervised learning classification models with automated preprocessing and performance reporting.
Orchestrates sophisticated multi-agent systems and intelligent task routing using the Vercel AI SDK v5.
Optimizes machine learning model performance by automatically searching for the best hyperparameter configurations using grid, random, or Bayesian search strategies.
Analyzes single-cell RNA-seq data using the Scanpy Python toolkit to perform quality control, clustering, and high-dimensional visualization.
Queries the NCBI Gene database to retrieve comprehensive genetic information, including sequences, functional annotations, and biological pathways.
Accesses the National Library of Medicine's PubMed database for advanced biomedical literature search and programmatic data retrieval.
Powers AI-driven drug discovery using PyTorch for molecular property prediction, protein modeling, and chemical retrosynthesis.
Automates the end-to-end deployment of machine learning models to production environments through API generation and containerization.
Facilitates seamless interaction between Claude and Google's Gemini CLI to enable multi-model planning and execution.
Streamlines computational molecular biology tasks using the Biopython toolkit for sequence analysis, structural bioinformatics, and NCBI database integration.
Deploys and scales Python code in serverless containers with high-performance GPU support and automatic autoscaling.
Automates the fine-tuning and adaptation of pre-trained machine learning models for specific datasets and tasks.
Provides a persistent cognitive architecture for AI agents to maintain long-term memory, context, and identity across multiple sessions.
Automates the generation and testing of scientific hypotheses by combining observational data patterns with academic literature insights.
Accesses the Human Metabolome Database (HMDB) to retrieve metabolite data, chemical properties, and biomarker information for scientific research.
Forecasts future values and identifies temporal patterns by analyzing historical time-series data using advanced statistical models.
Analyzes textual data to perform sentiment analysis, keyword extraction, and topic modeling using advanced natural language processing.
Validates ethical implications, fairness metrics, and bias detection within AI/ML models and datasets to ensure responsible development.
Analyzes text data to extract sentiments, keywords, and topics using advanced natural language processing techniques.
Automates electronic lab notebook management through the LabArchives REST API for research documentation, data backups, and institutional reporting.
Builds production-ready Apache Airflow pipelines using industry-standard patterns for orchestration, error handling, and automated testing.
Optimizes vector database performance by tuning HNSW parameters, quantization strategies, and memory-to-recall trade-offs.
Automates the partitioning of data into training, validation, and testing sets to streamline machine learning model development.
Optimizes Apache Spark jobs through advanced partitioning, memory management, and shuffle performance tuning.
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