Data & AI Skills
Discover the best AI skills in the Data & AI category.
184 skills
Prompt Engineering
Data & AI
Prompt engineering best practices and templates to maximize AI outputs.
Data Visualization
Data & AI
Generates data visualizations and charts tailored to your data.
RAG Architecture Setup
Data & AI
Setup guide for RAG (Retrieval-Augmented Generation) architectures.
Data Pipeline Builder
Data & AI
Generates ETL/ELT configurations and robust data pipeline architectures.
ML Experiment Tracker
Data & AI
Document and track your machine learning experiments in a structured way.
RFM Customer Segmentation
Data & AI
Analyze customer value using RFM (Recency, Frequency, Monetary) segmentation. Automatically cleans data, calculates RFM metrics, applies K-means clustering, and generates visual reports with actionable insights.
Automated Data Preprocessing Pipeline
Data & AI
Automate data cleaning, transformation, and validation for ML tasks. Generates and executes robust ETL pipelines with quality reports and performance metrics.
Document splitting
Data & AI
Reads documents and splits them into manageable chunks based on line count, character size, markdown sections, or paragraphs. Supports overlapping chunks to maintain context. Useful for processing large files, analysis, or transfer tasks.
Data Analysis
Data & AI
Load, clean, and analyze datasets of various formats. Create visualizations, detect patterns, and build predictive models using statistical methods. Ideal for exploratory data analysis, time series forecasting, and generating professional reports.
ArXiv Paper Search & Summarize
Data & AI
Search and summarize arXiv papers by topic, title, author, or identifier. Produces structured summaries (problem, method, results, limitations) with direct links to papers. Useful for exploring recent literature or getting a quick overview of a specific paper.
Eigenvalues and Eigenvectors
Data & AI
Problem-solving strategies for eigenvalues in linear algebra. Compute characteristic polynomials, eigenvalues and eigenvectors with verification methods.
Historical Data Validation
Data & AI
Validates historical data completeness and quality over date ranges, identifies gaps and cascade effects (corrupted rolling averages up to 21 days forward), and provides ordered remediation plans. Helps audit data integrity after pipeline failures or before using data for predictions.