td-convolution
Convolution operations for signal processing and filtering
浏览 teradata-labs 维护的已发布 AI 技能,比较用途与说明,并通过来源仓库了解安装方式。
已收录技能
63收录技能的仓库 Stars 合计
378仓库 Forks
0平均每个技能的仓库 Stars
6同一仓库中的多个技能可能共享 Stars,合计包含重复仓库数据。
Convolution operations for signal processing and filtering
Outlier detection and handling using TD_OutlierFit
Time series differencing for stationarity and trend removal
Digital filtering for noise reduction and signal enhancement
Signal correlation analysis for similarity and delay detection
ARIMA parameter estimation for seasonal and non-seasonal AR, MA, ARMA, and ARIMA models
Monitor active Teradata sessions using real-time resources, view SQL execution details, identify blocking issues, and optionally take control actions
Analyze system performance using throttle statistics, query logs, and resource metrics to identify bottlenecks and optimization opportunities
Decision forest ensemble classifier for robust predictions
Ljung-Box portmanteau tests for model diagnostics and residual analysis
Logistic regression for binary and multinomial classification
Classification model evaluation and metrics calculation
Random forest ensemble classifier for high-accuracy classification
Advanced parameter estimation and optimization for UAF models
Statistical tests for time series stationarity (ADF, KPSS, PP tests)
Session analysis and user journey tracking
Monitor AMP processor load, system physical resources, and capacity using real-time resources to track system health and identify performance bottlenecks
Analyze workload classification and **autonomously configure** classification rules, filters, and priorities to improve accuracy and meet business requirements
Fourier transformation for frequency domain analysis
Power spectrum analysis for frequency domain insights and periodicity detection
Change point detection in time series for structural breaks
Marketing attribution modeling and analysis
Advanced column transformation and feature engineering
Data scaling and normalization using TD_ScaleFit and TD_ScaleTransform
默认按已收录数据中的 GitHub 仓库 Stars 排序。Stars 属于来源仓库,同一仓库的多个技能可能共享相同数值;它反映仓库关注度,不代表单个技能的安装量或质量评分。