machine-learning
2
causal-inference
Bengio's causal inference for AI: Interventional reasoning, counterfactuals, and System 2 deep learning. World models with causal structure.
plurigrid
data-ai
sorting
stars
current ordering strategy
query
all entries
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machine-learning
2
model-evaluator
Evaluate and compare ML model performance with rigorous testing methodologies
eddiebe147
data-ai
machine-learning
2
td-scale-fit
Data scaling and normalization using TD_ScaleFit and TD_ScaleTransform
teradata-labs
data-ai
machine-learning
2
td-random-forest
Random forest ensemble classifier for high-accuracy classification
teradata-labs
data-ai
machine-learning
2
fine-tuning
LLM fine-tuning with LoRA, QLoRA, and instruction tuning for domain adaptation.
pluginagentmarketplace
data-ai
machine-learning
2
td-decision-forest
Decision forest ensemble classifier for robust predictions
teradata-labs
data-ai
machine-learning
2
td-portman
Ljung-Box portmanteau tests for model diagnostics and residual analysis
teradata-labs
data-ai
machine-learning
2
self-validation-loop
Run self-validation loops for triadic color systems using prediction
plurigrid
data-ai
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