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O SkillsMP coletou 14 skills de zenml-io/skills. Abra uma skill para revisar a origem e os detalhes.
Mostrando 14 de 14 skills coletadas.
Migrate Apache Airflow DAGs, operators, and workflows to idiomatic ZenML pipelines. Handles concept mapping (DAG→pipeline, operator→step, XCom→artifact), code translation, scheduling, retry config, Docker settings, and flags unsupported patterns (trigger…
Idioma do texto original: inglês
Migrate Kedro pipelines and projects to idiomatic ZenML pipelines. Handles concept mapping (node->step, Pipeline->pipeline, Data Catalog->explicit boundary steps plus artifacts, params:->typed parameters), catalog analysis, code translation,…
Idioma do texto original: inglês
Author ZenML pipelines: @step/@pipeline decorators, type hints, multi-output steps, dynamic vs static pipelines, artifact data flow, ExternalArtifact, YAML configuration, DockerSettings and ResourceSettings for remote execution, custom materializers, metadata…
Idioma do texto original: inglês
Migrate Prefect flows, tasks, and deployment patterns to idiomatic ZenML pipelines. Handles concept mapping (`@flow`→`@pipeline`, `@task`→`@step`, result persistence→artifacts), dynamic-execution analysis, code translation, scheduling, retries, Blocks/secrets…
Idioma do texto original: inglês
Implements ZenML quick wins to enhance MLOps workflows. Investigates codebase and stack configuration, recommends high-priority improvements, and implements metadata logging, experiment tracking, alerts, scheduling, secrets management, tags, git hooks, HTML…
Idioma do texto original: inglês
Migrate Argo Workflows, WorkflowTemplates, ClusterWorkflowTemplates, and CronWorkflows to idiomatic ZenML pipelines. Handles concept mapping, YAML-to-Python translation, scheduling, retries, Kubernetes-native pattern analysis, and flags unsupported patterns…
Idioma do texto original: inglês
Migrate Azure Machine Learning SDK v2 pipelines, components, environments, and schedules to idiomatic ZenML pipelines. Handles concept mapping (`@pipeline` -> `@pipeline`, `@command_component` -> `@step`, `Environment(...)` -> `DockerSettings(...)`, AzureML…
Idioma do texto original: inglês
Migrate Dagster assets, ops, graphs, jobs, and software-defined asset workflows to idiomatic ZenML pipelines. Handles concept mapping (asset->step output, job->pipeline, IOManager->artifact store/materializer + explicit IO steps), asset-boundary planning,…
Idioma do texto original: inglês
Migrate Databricks Workflows (Lakeflow Jobs) to idiomatic ZenML pipelines. Handles concept mapping (Job->pipeline, Task->step, task values->artifact), notebook refactoring, code translation for all Databricks task types (notebook_task, python_wheel_task,…
Idioma do texto original: inglês
Migrate Flyte workflows, tasks, LaunchPlans, and Flytekit code to idiomatic ZenML pipelines. Handles concept mapping (`@task`->`@step`, `@workflow`->`@pipeline`, `map_task()`->dynamic `.map()`, `conditional()`->dynamic branching, `LaunchPlan`->schedule/config…
Idioma do texto original: inglês
Migrate Metaflow flows and Outerbounds-flavored Metaflow projects to idiomatic ZenML pipelines. Handles concept mapping (FlowSpec->pipeline, @step->@step, self.* artifacts->explicit returns and inputs), code translation for Parameters, IncludeFile, Config,…
Idioma do texto original: inglês
Migrate Amazon SageMaker Pipelines and workflow code to idiomatic ZenML pipelines. Handles concept mapping (Pipeline->@pipeline, ProcessingStep/TrainingStep->@step, PropertyFile/JsonGet->artifacts), code translation, SagemakerOrchestratorSettings mapping,…
Idioma do texto original: inglês
Scope and decompose ML workflow ideas into realistic ZenML pipeline architectures. Runs an in-depth interview to help users break down ambitious or over-engineered plans into well-composed multi-pipeline setups, identify what belongs in a pipeline vs. what…
Idioma do texto original: inglês
Migrate Vertex AI Pipelines (Kubeflow Pipelines v2 / PipelineJob workflows) to idiomatic ZenML pipelines. Handles concept mapping (`@dsl.pipeline` -> `@pipeline`, `@dsl.component` -> `@step`, `PipelineJob.create_schedule(...)` -> `Schedule(...)`),…
Idioma do texto original: inglês