weights-and-biases

Track ML experiments with automatic logging, visualize training in real-time, optimize hyperparameters with sweeps, and manage model registry with W&B - collaborative MLOps platform

experiment-trackinghyperparameter-tuningmodel-registryvisualization

ovachiever

81

ray-train

Distributed training orchestration across clusters. Scales PyTorch/TensorFlow/HuggingFace from laptop to 1000s of nodes. Built-in hyperparameter tuning with Ray Tune, fault tolerance, elastic scaling. Use when training massive models across multiple machines or running distributed hyperparameter sweeps.

training-orchestrationdistributed-computinghyperparameter-tuningscalability

ovachiever

81

scikit-learn

Machine learning in Python with scikit-learn. Use when working with supervised learning (classification, regression), unsupervised learning (clustering, dimensionality reduction), model evaluation, hyperparameter tuning, preprocessing, or building ML pipelines. Provides comprehensive reference documentation for algorithms, preprocessing techniques, pipelines, and best practices.

scikit-learnsupervised-learningunsupervised-learningml-pipelines

ovachiever

81

classification-helper

Quick classifier training with automatic model selection, hyperparameter tuning, and comprehensive evaluation metrics.

model-selectionhyperparameter-tuningclassificationevaluation-metrics

dkyazzentwatwa

3

supervised-learning

Build production-ready classification and regression models with hyperparameter tuning

supervised-learningclassificationregressionhyperparameter-tuning

pluginagentmarketplace

11

training-pipelines

Master training pipelines - orchestration, distributed training, hyperparameter tuning

training-orchestrationdistributed-traininghyperparameter-tuningmodel-training

pluginagentmarketplace

1

model-optimization

Quantization, pruning, AutoML, hyperparameter tuning, and performance optimization. Use for improving model performance, reducing size, or automated ML.

hyperparameter-tuningperformance-optimizationml-pipelinesmodel-compression

pluginagentmarketplace

21

fine-tuning-expert

Use when fine-tuning LLMs, training custom models, or optimizing model performance for specific tasks. Invoke for parameter-efficient methods, dataset preparation, or model adaptation.

llmdata-preprocessinghyperparameter-tuningperformance-tuning

Jeffallan

245

Model Hyperparameter Tuning

Optimize hyperparameters using grid search, random search, Bayesian optimization, and automated ML frameworks like Optuna and Hyperopt

hyperparameter-tuninggrid-searchbayesian-optimizationoptuna

aj-geddes

301

scikit-learn

Machine learning in Python with scikit-learn. Use when working with supervised learning (classification, regression), unsupervised learning (clustering, dimensionality reduction), model evaluation, hyperparameter tuning, preprocessing, or building ML pipelines. Provides comprehensive reference documentation for algorithms, preprocessing techniques, pipelines, and best practices.

pythonmachine-learningdata-analysishyperparameter-tuning

K-Dense-AI

3,233360