Discover Agent Skills for data science & ml. Browse 61 skills for Claude, ChatGPT & Codex.
Architects high-impact system prompts to define agent identity, rules, and behavior patterns for custom AI assistants.
Searches and summarizes research papers from ArXiv to provide concise insights on technical topics and recent publications.
Guides the end-to-end delivery of ML/AI projects through structured experimentation, data exploration, and responsible AI practices.
Standardizes the creation of Google Colab notebooks for machine learning and trading experiments using a high-performance template.
Configures authentication credentials for external AI services including OpenAI GPT and Google Gemini.
Provides specialized tools for molecular manipulation, chemical property calculation, and machine learning in drug discovery workflows.
Deploys and optimizes PyTorch models for production environments, edge devices, and high-performance C++ applications.
Scales Python's data science stack to multi-core systems and distributed clusters using lazy evaluation and task scheduling.
Integrates high-performance analytical SQL capabilities into Python workflows for efficient data processing and large-scale querying.
Generates publication-quality 2D plots, scientific visualizations, and complex multi-panel figures using industry-standard Python patterns.
Generates high-performance animations, publication-quality scientific figures, and interactive data visualization tools using advanced Matplotlib techniques.
Empowers Claude to perform real-time image processing, video analysis, and advanced computer vision tasks using the industry-standard OpenCV library.
Implements industry-standard gradient boosting algorithms for high-performance machine learning on tabular and structured datasets.
Converts and processes chemical data across 110+ formats for molecular modeling, informatics, and 3D structure generation.
Implements industry-standard machine learning workflows in Python for predictive data analysis including classification, regression, and clustering.
Implements intelligent, low-overhead progress bars for Python loops, data processing, and machine learning workflows.
Streamlines computational biology workflows with specialized guidance for sequence analysis, file parsing, and biological database integration using Biopython.
Integrates differentiable quantum computing circuits into classical machine learning workflows for hybrid model development.
Generates interactive, web-based charts and complex data dashboards using Python's high-level Plotly library.
Simplifies scientific image processing and analysis using Python-based algorithms and NumPy-compatible workflows.
Solves complex combinatorial optimization problems including vehicle routing, scheduling, and resource allocation using Google's open-source suite.
Performs complex symbolic mathematical operations including calculus, equation solving, and algebraic manipulation using the SymPy library.
Optimizes Dask distributed computing performance through advanced cluster tuning, memory management, and task graph refinement.
Performs advanced survival analysis and time-to-event modeling using the lifelines library for medical, clinical, and epidemiological research.
Analyzes and visualizes human neurophysiological data including EEG, MEG, and intracranial recordings using Python-based best practices.
Analyzes molecular dynamics trajectories and structural data using the MDAnalysis Python library for biophysical research.
Manages and analyzes multi-dimensional labeled arrays and datasets for scientific computing and physical sciences.
Deploys scientific models and data applications using high-performance FastAPI backends and interactive Streamlit frontends.
Analyzes protein dynamics, evolution, and structural flexibility using Elastic Network Models and structural ensemble analysis.
Accelerates Python and NumPy code using Just-In-Time (JIT) compilation for machine-speed execution.
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