Plugins

2 plugins

SQL, analytics, datasets, models and machine-learning workflows.

29 skills · plugin

Deploy Azure ML Pipeline

Manage Azure Machine Learning resources including workspaces, jobs, models, data, compute, and pipelines using the SDK v2 for Python.

3 skills · plugin

Results for “learning”

10 skills

continual-learning

Implements a continual learning loop for AI coding agents using hooks, two-tier memory (global and local), and automatic pattern detection to persist and apply learnings across sessions.

cuopt-skill-evolution

Detects generalizable learnings from problem-solving interactions and proposes skill updates to improve future performance.

Train reinforcement learning agents at millions of steps per second using optimized PPO, vectorized environments, and multi-agent support.

30.2k · bundle

transformers-js

Run state-of-the-art machine learning models directly in JavaScript/TypeScript across browsers and server-side runtimes using Transformers.js.

10.8k · bundle

More results

Evaluates the agent's own work, catches mistakes, and improves permanently through self-reflection, self-criticism, and learning from corrections.

azure-ai-projects-java

Manage Azure AI Foundry projects, connections, datasets, indexes, and evaluations using the Java SDK.

Improves skills by analyzing execution data to identify patterns in successful versus failed runs, staging changes for human approval.

Turn model work into a production ML system with data contracts, repeatable training, measurable quality gates, deployable artifacts, and operational monitoring.

tilegym-cutile-python

Write high-performance GPU kernels using cuTile's tile-based programming model with validation and optimization, including deep agent orchestration for complex multi-kernel tasks.

nemo-rl-auto-research

Guides agents through the full lifecycle of NeMo-RL experiments: understanding recipes, launching reproducible runs, analyzing results, and preserving human oversight with git and TSV logs.