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AI/ML Workflow Bundle

sickn33/antigravity-awesome-skills

AI and machine learning workflow covering LLM application development, RAG implementation, agent architecture, ML pipelines, and AI-powered features.

AI/ML Workflow Bundle

sickn33/antigravity-awesome-skills

AI and machine learning workflow covering LLM application development, RAG implementation, agent architecture, ML pipelines, and AI-powered features.

Azure ML SDK Python

sickn33/antigravity-awesome-skills

Client library to manage Azure Machine Learning resources—workspaces, datasets, compute, jobs, models, environments, and pipelines—directly from Python with MLClient authentication, configuration, and best practices for reproducible workflows.

Azure ML SDK Python

sickn33/antigravity-awesome-skills

Client library to manage Azure Machine Learning resources—workspaces, datasets, compute, jobs, models, environments, and pipelines—directly from Python with MLClient authentication, configuration, and best practices for reproducible workflows.

AutoML Pipeline Builder

building-automl-pipelines

jeremylongshore/claude-code-plugins-plus-skills

Builds AutoML pipelines by analyzing user requests, generating code for data preparation, model selection, hyperparameter tuning, validation, and metrics, then documenting artifacts for streamlined automated machine learning workflows.

Advanced Data Science Expert

sickn33/antigravity-awesome-skills

Provides expert guidance on advanced analytics, machine learning, and statistical modeling, covering the full data science workflow from exploratory analysis to production-ready models and stakeholder reporting.

Automated Model Deployment

deploying-machine-learning-models

jeremylongshore/claude-code-plugins-plus-skills

Deploying Machine Learning Models automates serving trained models to production by analyzing requirements, generating API and infrastructure code, and orchestrating deployment workflows with validation, error handling, and monitoring baked in.

Feature Engineering Toolkit

engineering-features-for-machine-learning

jeremylongshore/claude-code-plugins-plus-skills

Feature Engineering Toolkit automates creating, selecting, and transforming dataset features to improve machine learning models; use it whenever you need new interactions, automatic selection, scaling, or encoding to boost accuracy and interpretability.

Machine Learning Model Evaluation

evaluating-machine-learning-models

jeremylongshore/claude-code-plugins-plus-skills

Provides detailed evaluation of machine learning models using plugin metrics to assess accuracy, precision, recall, F1, and other key indicators, helping users compare models and validate performance before deployment.

Explaining Machine Learning Models

explaining-machine-learning-models

jeremylongshore/claude-code-plugins-plus-skills

Provides interpretable explanations for ML predictions using SHAP, LIME, and other techniques, helping debug model behavior, highlight feature importance, and communicate fairness insights to stakeholders.

Feature Importance Analyzer

feature-importance-analyzer

jeremylongshore/claude-code-plugins-plus-skills

Automates guidance on assessing feature importance for machine learning training, covering data prep, model training, tuning, and experiment tracking while generating production-ready code, configurations, and validation instructions for best-practice compliance.

Flask ML API Creator

flask-ml-api-creator

jeremylongshore/claude-code-plugins-plus-skills

Automates Flask-based machine learning API deployment by guiding you through best practices, generating production code/configurations, and validating outputs for serving, monitoring, and MLOps pipelines.

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