data science & ml Claude 스킬을 발견하세요. 61개의 스킬을 탐색하고 AI 워크플로우에 완벽한 기능을 찾아보세요.
Enforces Alpaca broker-specific constraints by filtering unsupported crypto short orders while maintaining valid equity shorting capabilities.
Accelerates quantitative trading universe selection by 3-4x through parallel processing and optimized caching strategies.
Resolves KeyError: 'uid' errors when updating interactive Plotly FigureWidget shapes and sliders in VS Code.
Leverages the Alpaca Algo Trader Plus subscription to fetch extended historical market data for training robust trading models.
Eliminates horizontal banding artifacts in microscopy data by implementing true lightsheet Point Spread Function (PSF) calculations.
Optimizes trading universe selection by applying sector-specific volume filters to ensure a diverse and manageable pool of candidates.
Enforces strict portfolio diversity constraints and correlation limits in trading systems using the Fail Loudly pattern.
Classifies text data using zero-shot labeling or custom-trained machine learning models directly within your terminal.
Queries and analyzes personal book libraries from Goodreads CSV exports to provide reading insights and statistics.
Implements end-to-end machine learning pipelines in R using the modern tidymodels ecosystem.
Processes and generates multimedia content including audio, video, images, and documents using the Google Gemini API.
Automates the creation of FiftyOne datasets from local media files and executes machine learning model inference pipelines.
Optimizes LangGraph application performance by iteratively refining prompts and node-level processing logic based on quantitative evaluation criteria.
Converts audio files into high-quality timestamped transcriptions using NVIDIA's Parakeet model optimized for Apple Silicon.
Builds and manages discrete-event simulations in Python for modeling complex systems like logistics, manufacturing, and network traffic.
Integrates Google's Gemini models into your workflow for advanced reasoning and multi-perspective code analysis.
Develops predictive player projection models using specialized feature engineering and sports-specific machine learning validation techniques.
Implements the System Skill Pattern to build persistent, data-driven CLI tools that evolve through continuous user interaction.
Performs probabilistic modeling and deep generative analysis for single-cell omics data using the scvi-tools framework.
Builds high-performance Retrieval-Augmented Generation (RAG) systems to ground LLM responses with proprietary or external data.
Optimizes vector search performance by tuning index parameters, quantization strategies, and memory usage for production-grade AI applications.
Infers gene regulatory networks from transcriptomics data using scalable algorithms like GRNBoost2 and GENIE3.
Builds sophisticated LLM applications using the LangChain framework with agents, memory systems, and complex workflows.
Builds robust, production-grade backtesting systems for trading strategies while mitigating common biases and handling transaction costs.
Facilitates seamless integration with vector databases for semantic search, retrieval-augmented generation (RAG), and high-dimensional embedding management.
Processes gigapixel whole slide images to automate tissue detection and tile extraction for digital pathology.
Provides domain-specific knowledge and experimental constraints for mechanistic interpretability research on Splatoon data models.
Manages Retrieval-Augmented Generation (RAG) indices to enable semantic search capabilities over BigQuery datasets.
Develops, trains, and deploys specialized machine learning models for healthcare and clinical data analysis using standardized EHR datasets and medical coding systems.
Performs high-performance computational fluid dynamics simulations and spectral analysis using Python.
Scroll for more results...