Plugins
2 plugins@dotnet
Dotnet AI
AI and ML skills for .NET: technology selection, LLM integration, agentic workflows, RAG pipelines, MCP, and classic ML with ML.NET.
5 skills · plugin
curated
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 “ml-pipelines”
57 skills
nimoqup046-collab AI Ml
Orchestrates AI/ML development workflows covering LLM applications, RAG systems, AI agents, ML pipelines, and observability.
2
lucaspmarie-a11y AI Ml
Orchestrates AI/ML workflows for building LLM applications, RAG systems, AI agents, and ML pipelines, covering design, integration, observability, and security.
5
antigravity AI Ml
Orchestrates AI/ML workflows for building LLM applications, RAG systems, AI agents, and ML pipelines with observability and security.
42.4k
lingxling AI Ml
Orchestrates AI/ML workflows for building LLM applications, RAG systems, AI agents, and ML pipelines, covering design, integration, observability, and security.
253
jorcan AI Ml
Orchestrates AI/ML workflows for building LLM applications, RAG systems, AI agents, and ML pipelines, covering design, integration, observability, and security.
0 · bundle
phoroth AI Ml
Orchestrates AI/ML workflows for building LLM applications, RAG systems, AI agents, and ML pipelines, covering design, integration, observability, and security.
3
More results
sinhoneyy AI Ml
AI and machine learning workflow covering LLM application development, RAG implementation, agent architecture, ML pipelines, and AI-powered features.
11
kursku AI Ml
AI and machine learning workflow covering LLM application development, RAG implementation, agent architecture, ML pipelines, and AI-powered features.
55
jantoniofc AI Ml
AI and machine learning workflow covering LLM application development, RAG implementation, agent architecture, ML pipelines, and AI-powered features.
6
manu14357 AI Ml
AI and machine learning workflow covering LLM application development, RAG implementation, agent architecture, ML pipelines, and AI-powered features.
16
desesbraker AI Ml
AI and machine learning workflow covering LLM application development, RAG implementation, agent architecture, ML pipelines, and AI-powered features.
2
welitonevoc AI Ml
AI and machine learning workflow covering LLM application development, RAG implementation, agent architecture, ML pipelines, and AI-powered features.
1
diegojcn AI Ml
AI and machine learning workflow covering LLM application development, RAG implementation, agent architecture, ML pipelines, and AI-powered features.
1
inskillflow AI Ml
AI and machine learning workflow covering LLM application development, RAG implementation, agent architecture, ML pipelines, and AI-powered features.
1
iamanacarolinarezende AI Ml
AI and machine learning workflow covering LLM application development, RAG implementation, agent architecture, ML pipelines, and AI-powered features.
0
doriangallo AI Ml
AI and machine learning workflow covering LLM application development, RAG implementation, agent architecture, ML pipelines, and AI-powered features.
1
jeffallan Ml Pipeline
Designs and implements production-grade ML pipeline infrastructure: configures experiment tracking, creates orchestration DAGs, builds feature store schemas, deploys model registries, and automates retraining and validation workflows.
10.4k · bundle
mmehdi0606 AI Ml
AI and machine learning workflow covering LLM application development, RAG implementation, agent architecture, ML pipelines, and AI-powered features.
2
francostino AI Ml
AI and machine learning workflow covering LLM application development, RAG implementation, agent architecture, ML pipelines, and AI-powered features.
63
majiayu000 Ml
Guides machine learning development with experiment tracking, hyperparameter optimization, model registry, and MLOps pipeline integration.
567 · bundle
antigravity Ml Engineer
Build production ML systems with PyTorch 2.x, TensorFlow, and modern ML frameworks, including model serving, feature engineering, A/B testing, and monitoring.
42.4k
paramchordiya Mlops And Infra
Enforces ML infrastructure, experiment tracking, reproducibility, model packaging, CI/CD, monitoring, and infrastructure-as-code standards at principal-engineer level.
0
dokhacgiakhoa Ml Engineer
Build production ML systems with PyTorch 2.x, TensorFlow, and modern ML frameworks. Implements model serving, feature engineering, A/B testing, and monitoring. Use PROACTIVELY for ML model deployment, inference optimization, or production ML infrastructure.
505 · bundle
bouclem AI Ml
AI and machine learning workflow covering LLM application development, RAG implementation, agent architecture, ML pipelines, and AI-powered features.
7
livelybug Mle Workflow
Production machine-learning engineering workflow for data contracts, reproducible training, model evaluation, deployment, monitoring, and rollback. Use when building, reviewing, or hardening ML systems beyond one-off notebooks.
0
diegojcn Ml Engineer
Build production ML systems with PyTorch 2.x, TensorFlow, and modern ML frameworks. Implements model serving, feature engineering, A/B testing, and monitoring.
1
bouclem Ml Engineer
Build production ML systems with PyTorch 2.x, TensorFlow, and modern ML frameworks. Implements model serving, feature engineering, A/B testing, and monitoring.
7
nvidia Nemo Mbridge Mlm Bridge Training
Run Megatron-LM (MLM) and Megatron Bridge training with mock or real data, covering correlation testing, available recipes, and multi-GPU examples.
2.2k · bundle
nvidia Deepstream Generate Pipeline
Builds and validates DeepStream GStreamer pipelines through an interactive questionnaire and a BM25 retrieval engine over 270+ verified pipelines.
2.2k · bundle
nvidia Tao Run Automl Deft Pipeline
Runs a three-phase AOI training pipeline: AutoML HPO baseline, DEFT iterative data improvement, and AutoML refinement on the augmented dataset.
2.2k · bundle
arjumaan AI Ml
AI and machine learning workflow covering LLM application development, RAG implementation, agent architecture, ML pipelines, and AI-powered features.
1
rajanthar Mle Workflow
Production machine-learning engineering workflow for data contracts, reproducible training, model evaluation, deployment, monitoring, and rollback. Use when building, reviewing, or hardening ML systems beyond one-off notebooks.
0
shulkwisec AI Ml Security
AI/ML security playbook. Use when assessing model supply chain attacks (pickle RCE, poisoned weights), adversarial examples, model poisoning, model stealing, data privacy attacks (membership inference, model inversion), and autonomous agent security risks.
21
affaan-m Mle Workflow
Turn model work into a production ML system with data contracts, repeatable training, measurable quality gates, deployable artifacts, and operational monitoring.
226k
mhassan0000 Mle Workflow
Turns model work into a production ML system with data contracts, reproducible training, quality gates, deployable artifacts, and monitoring.
1
ziri22 Agent Ml Ops
MLOps Engineer IA — Expert en déploiement de modèles ML (A/B testing, feature stores, MLflow, Kubeflow). Industrialise le ML du notebook à la production.
6