machine-learning
2
self-validation-loop
Run self-validation loops for triadic color systems using prediction
plurigrid
data-ai
sorting
stars
current ordering strategy
query
all entries
refine the visible subset
machine-learning
2
td-regression-evaluator
Comprehensive regression model evaluation using TD_RegressionEvaluator
teradata-labs
data-ai
machine-learning
2
td-movavg-forecast
Moving average based forecasting for smoothed predictions
teradata-labs
data-ai
machine-learning
2
td-convolution
Convolution operations for signal processing and filtering
teradata-labs
data-ai
machine-learningmarketplace
2
detection-tuner
Investigate noisy/common alerts and create false positive (FP) rules to suppress benign detections. Analyzes detection frequency over 7 days, identifies patterns, generates and tests FP rules with operator approval before deployment. Use for tuning detection noise, reducing alert fatigue, suppressing known-safe activity, or when specific detections need filtering. Human-in-the-loop workflow ensures no FP rules are deployed without explicit approval.
refractionPOINT
data-ai
machine-learning
2
ai-engineer
You are a highly skilled AI Engineer specializing in the practical application of machine learning models. You are an expert in Python and popular AI/ML frameworks like TensorFlow, PyTorch, and scikit-learn. You excel at data preprocessing, model training, evaluation, and deployment.
aibangjuxin
data-ai
machine-learning
2
moai-domain-ml
Enterprise Machine Learning specialist with TensorFlow 2.20.0, PyTorch 2.9.0, Scikit-learn 1.7.2 expertise. Master AutoML, neural architecture search, MLOps automation, and production ML deployment. Build scalable ML pipelines with comprehensive monitoring and experiment tracking.
AJBcoding
data-ai
machine-learning
2
td-outlier-detection
Outlier detection and handling using TD_OutlierFit
teradata-labs
data-ai
machine-learning
2
cognitive-surrogate
Layer 6 Barton Cognitive Surrogate - build, train, validate psychological models with >90% fidelity
plurigrid
data-ai
machine-learning
2
td-linear-regression
Linear regression analysis for continuous target prediction
teradata-labs
data-ai
machine-learning
2
ran-reinforcement-learning-engineer
Reinforcement learning engineering for RAN systems with policy gradients, experience replay, and AgentDB integration. Implements hybrid RL with multi-objective optimization for energy, mobility, coverage, and capacity.
ricable
data-ai
machine-learning
2
base-model-selector
Use when starting a fine-tuning project to determine if fine-tuning is needed, or when evaluating whether a base model meets quality thresholds for a specific domain task
marcgreen
data-ai
machine-learning
2
td-column-transformer
Advanced column transformation and feature engineering
teradata-labs
data-ai
machine-learning
2
td-naive-bayes
Naive Bayes classifier for probabilistic classification
teradata-labs
data-ai
machine-learning
2
td-data-preparation
UAF-specific data preparation and validation for time series analysis
teradata-labs
data-ai
machine-learning
2
levin-levity
Leonid Levin''s algorithmic complexity meets playful mutual ingression. Use for: BB(n) prediction markets, Kolmogorov complexity rewards, WEV extraction from proof inefficiencies, Nash equilibrium between exploration (LEVITY) and convergence (LEVIN).
plurigrid
data-ai
machine-learning
2
td-parameter-estimation
Advanced parameter estimation and optimization for UAF models
teradata-labs
data-ai
machine-learning
2
td-cross-validation
Time series specific cross-validation techniques for model validation
teradata-labs
data-ai
machine-learning
2
td-onehot-encoding
Categorical variable encoding using TD_OneHotEncodingFit and Transform
teradata-labs
data-ai
machine-learning
1
nixtla-forecast-validator
Validate forecast quality by comparing MASE and sMAPE against benchmarks. Use when detecting model degradation. Trigger with 'validate forecast' or 'check forecast quality'.
intent-solutions-io
data-ai
machine-learning
1
nixtla-model-selector
Automatically selects the best forecasting model between StatsForecast and TimeGPT based on time series data characteristics. Use when unsure which model performs best. Trigger with 'auto-select model', 'choose best model', 'model selection'.
intent-solutions-io
data-ai
machine-learning
1
nixtla-experiment-architect
Scaffolds production-ready forecasting experiments with Nixtla libraries. Creates configuration files, experiment harnesses, multi-model comparisons, and cross-validation workflows for StatsForecast, MLForecast, and TimeGPT. Activates when user needs experiment setup, forecasting pipeline creation, model benchmarking, or multi-model comparison framework.
intent-solutions-io
data-ai
machine-learning
1
nixtla-model-selector
Automatically selects the best forecasting model between StatsForecast and TimeGPT based on time series data characteristics. Use when unsure which model performs best. Trigger with "auto-select model", "choose best model", "model selection".
intent-solutions-io
data-ai