Discover Agent Skills for data science & ml. Browse 61 skills for Claude, ChatGPT & Codex.
Builds professional-grade financial models including DCF analysis, Monte Carlo simulations, and scenario planning for investment valuation.
Manages and publishes research papers on the Hugging Face Hub by linking them to models and datasets, claiming authorship, and generating structured markdown articles.
Manages and automates the integration of structured evaluation results into Hugging Face model cards and metadata.
Manages the end-to-end lifecycle of Hugging Face Hub datasets, providing tools for repository initialization, configuration, and structured data streaming.
Trains and fine-tunes language models on Hugging Face's cloud infrastructure using the TRL library.
Accelerates the development of high-performance ML and AI applications in Rust by providing domain-specific design patterns and framework guidance.
Provides deterministic, symbolic mathematical computation using SymPy to ensure absolute accuracy in complex calculations.
Executes deterministic mathematical computations using SymPy to ensure exact symbolic results across algebra, calculus, linear algebra, and statistics.
Configures a Docker-based MCP server for searching and downloading academic papers from arXiv, PubMed, and other scholarly sources.
Transforms complex business data into actionable insights through advanced analytics, predictive modeling, and strategic KPI frameworks.
Architects sophisticated LLM applications using the LangChain framework for agents, memory management, and complex workflow orchestration.
Optimizes development efficiency by routing complex Rust architecture tasks to Sonnet 4.5 and routine utility work to Haiku 4.5.
Optimizes vector index performance by tuning HNSW parameters, quantization strategies, and memory usage for high-scale search.
Optimizes LLM performance through advanced prompting techniques, constitutional AI, and production-ready prompt system design.
Transcribes audio files into text or JSON format using OpenAI's state-of-the-art Whisper API.
Generates testable, evidence-based scientific hypotheses and structured experimental designs from observations or literature.
Implements comprehensive evaluation strategies for LLM applications using automated metrics, human feedback, and benchmarking frameworks.
Builds and automates production-grade machine learning pipelines, experiment tracking systems, and scalable ML infrastructure across cloud platforms.
Provides expert-level data analysis, machine learning modeling, and statistical insights to drive data-driven decision-making.
Builds production-grade LLM applications, advanced RAG architectures, and autonomous agent systems with a focus on scalability and safety.
Performs declarative causal interventions and mechanistic interpretability experiments on PyTorch models.
Implements Anthropic's Constitutional AI method to train harmless, helpful models through self-critique and automated AI feedback.
Builds LLM-powered applications using agents, retrieval-augmented generation (RAG), and modular chains.
Connects LLMs to private data sources through advanced document ingestion, vector indexing, and retrieval-augmented generation (RAG) pipelines.
Optimizes large-scale language model training using NVIDIA Megatron-Core with advanced 3D and expert parallelism strategies.
Accelerates Large Language Model inference on NVIDIA GPUs using state-of-the-art optimization techniques for maximum throughput and minimal latency.
Implements programmable safety rails and validation for LLM applications to prevent jailbreaks, hallucinations, and PII leaks.
Implements and trains minimalist GPT architectures for educational and research purposes using Andrej Karpathy's clean, hackable codebase.
Transcribes audio, translates speech to English, and automates multilingual audio processing using OpenAI's Whisper models.
Simplifies Large Language Model implementation, training, and fine-tuning using clean, production-ready LitGPT architectures.
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