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claude-cookbooks
claude-cookbooks contient 49 skills collectées depuis teradata-labs, avec une couverture métier par dépôt et des pages de détail sur le site.
Skills dans ce dépôt
Auto-correlation analysis for time series dependency and pattern detection
Analysis of variance for comparing group means
ARIMA-based time series forecasting for trend and seasonal predictions
ARIMA parameter estimation for seasonal and non-seasonal AR, MA, ARMA, and ARIMA models
Marketing attribution modeling and analysis
Automated ARIMA model selection and forecasting
Change point detection in time series for structural breaks
Chi-square test of independence for categorical variables
Convolution operations for signal processing and filtering
Comprehensive data profiling and quality assessment using Teradata ClearScape Analytics descriptive statistics functions
Decision forest ensemble classifier for robust predictions
Signal detrending for baseline correction and trend removal
Fourier transformation for frequency domain analysis
Time series differencing for stationarity and trend removal
Fast Fourier Transform for frequency domain analysis and spectral decomposition
F-test for comparing variances between two groups
Hierarchical clustering for nested data grouping
Approximate nearest neighbor search using HNSW algorithm
Inverse Fast Fourier Transform for time domain reconstruction
K-Nearest Neighbors for classification and regression
Linear regression analysis for continuous target prediction
Logistic regression for binary and multinomial classification
Moving average based forecasting for smoothed predictions
Path analysis for sequential event patterns
Categorical variable encoding using TD_OneHotEncodingFit and Transform
Score data using ONNX models (Bring Your Own Model)
Ordinal encoding for ordered categorical variables
Outlier detection and handling using TD_OutlierFit
Partial auto-correlation analysis for direct lag relationships
Score data using PMML models (Bring Your Own Model)
Ljung-Box portmanteau tests for model diagnostics and residual analysis
Power spectrum analysis for frequency domain insights and periodicity detection
Signal resampling and interpolation for rate conversion
ROC curve and AUC analysis for binary classification evaluation
Seasonal pattern decomposition and analysis
Sentiment analysis for text documents and sentences
Session analysis and user journey tracking
SHAP values for model explainability and feature importance
Silhouette coefficient for clustering quality evaluation
Missing value imputation using TD_SimpleImputeFit