Descubre Habilidades de Claude para data science & ml. Explora 61 habilidades y encuentra las capacidades perfectas para tus flujos de trabajo de IA.
Validates time series forecast accuracy by comparing current performance against historical benchmarks to detect model degradation.
Converts diverse file formats including PDFs, Office documents, images, and audio into LLM-optimized Markdown.
Orchestrates sophisticated multi-agent workflows using the AI SDK v5 to manage handoffs and intelligent task routing across multiple AI providers.
Quantifies the causal effect of external events on time series data using TimeGPT and counterfactual modeling.
Automates the end-to-end workflow of building, training, and evaluating machine learning classification models from labeled datasets.
Validates ethical implications, fairness metrics, and bias detection in AI/ML models and datasets.
Automates laboratory liquid handling by generating Opentrons Protocol API v2 scripts for Flex and OT-2 robots.
Forecasts Polymarket prediction market outcomes and price movements using Nixtla TimeGPT.
Analyzes multi-asset correlations and generates optimized hedging strategies for portfolio risk management.
Evaluates machine learning model performance using standardized metrics like accuracy, precision, and F1-score to guide model optimization and validation.
Analyzes and processes images using advanced computer vision techniques for object detection, classification, and segmentation.
Analyzes the AgentScope multi-agent framework by searching tutorials, implementation examples, and module structures.
Manipulates genomic datasets including SAM, BAM, CRAM, and VCF files through a Pythonic interface to htslib.
Performs rigorous statistical modeling and econometric analysis using regression, time-series, and hypothesis testing tools.
Streamlines PyTorch development by organizing code into modular structures and automating training workflows for scalable deep learning.
Queries NCBI ClinVar to retrieve genetic variant clinical significance, interpret pathogenicity, and annotate VCF files for genomic medicine.
Creates, analyzes, and visualizes complex network structures and graph algorithms using the NetworkX library in Python.
Audits Nixtla library implementation to suggest cost-effective model routing and forecasting performance optimizations.
Automates the partitioning of datasets into training, validation, and testing sets for machine learning workflows.
Processes and visualizes massive tabular datasets exceeding RAM limits using lazy, out-of-core DataFrames.
Optimizes machine learning model performance through automated grid search, random search, and Bayesian optimization.
Automates the partitioning of data into training, validation, and testing sets for machine learning workflows.
Implements high-performance persistent memory and learning patterns for stateful AI agents using AgentDB.
Solves complex single and multi-objective optimization problems using state-of-the-art evolutionary algorithms and decision-making tools.
Automates the cleaning, transformation, and validation of raw data into production-ready datasets for machine learning models.
Optimizes Nixtla TimeGPT models through automated dataset preparation, job submission, and performance benchmarking for domain-specific forecasting.
Powers Claude with high-performance vector search and semantic retrieval for RAG systems and intelligent document indexing.
Identifies system hardware capabilities and provides strategic recommendations for optimal computational performance in scientific tasks.
Transforms raw datasets into professional-grade charts, graphs, and visual plots using intelligent data analysis.
Implements high-performance persistent memory and pattern learning for stateful AI agents using AgentDB.
Scroll for more results...