Kubeflow
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Explore more → **Kubeflow**
What is Kubeflow?
Kubeflow is an open-source machine learning platform designed to simplify the deployment and management of machine learning workflows on Kubernetes. It provides a set of tools and components for tasks such as training, hyperparameter tuning, serving, and monitoring models. Kubeflow aims to make machine learning deployments scalable, reproducible, and portable across different environments.
What other technologies are related to Kubeflow?
Kubeflow Competitor Technologies
MLFlow
MLflow is a platform for the machine learning lifecycle, including experiment tracking, model packaging, and deployment. It overlaps with Kubeflow in model deployment and lifecycle management, thus is a competitor.
Seldon
Seldon provides a platform for deploying machine learning models on Kubernetes. It provides model serving capabilities, and is a competitor.
KServe
KServe (formerly KFServing) is a Kubernetes-based model serving framework focused on inference. It is a direct competitor since Kubeflow also offers model serving capabilities.
GCP Vertex AI
Vertex AI is a machine learning platform offered by Google Cloud Platform (GCP). It provides an end-to-end ML workflow, competing with Kubeflow's capabilities.
AWS Sagemaker
Amazon SageMaker is a fully managed machine learning service that enables developers and data scientists to quickly build, train, and deploy machine learning models. It overlaps with Kubeflow in providing a complete platform for ML, making it a competitor.
BentoML
BentoML is a platform for building and deploying machine learning services. Its model serving and deployment capabilities are similar to some of Kubeflow's components, making it a competitor.
DKube
No summary available
DKube is an end-to-end MLOps platform that provides capabilities for data versioning, model training, and deployment, competing with Kubeflow.
Azure ML
Azure Machine Learning is a cloud-based platform for building, training, and deploying machine learning models, thus competing with Kubeflow's end-to-end ML workflow capabilities.
Number of organizations that mention technology
3,378
Kubeflow
5,821
MLFlow
238
Seldon
147
KServe
3,441
GCP Vertex AI
7,423
AWS Sagemaker
111
BentoML
22
DKube
4,596
Azure ML
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Kubeflow Complementary Technologies
TFX
TensorFlow Extended (TFX) is a TensorFlow-based platform for building production ML pipelines. It integrates well with Kubeflow as a component within the pipeline.
TensorFlow
TensorFlow is a popular machine learning framework that can be used with Kubeflow for training and deploying models.
PyTorch
PyTorch is a machine learning framework that can be used within Kubeflow pipelines for model training and other tasks.
Number of organizations that mention technology
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Which job functions commonly mention Kubeflow?
MLOps Engineer
22.8% of all MLOps Engineer jobs mention Kubeflow
View 1.9k
jobs on Sumble
Machine Learning
5.0% of all Machine Learning jobs mention Kubeflow
View 5.2k
jobs on Sumble
AI Engineer
1.6% of all AI Engineer jobs mention Kubeflow
View 1.4k
jobs on Sumble
Data Scientist
0.7% of all Data Scientist jobs mention Kubeflow
View 1.7k
jobs on Sumble
Data, Analytics & Machine Learning
0.5% of all Data, Analytics & Machine Learning jobs mention Kubeflow
View 8.5k
jobs on Sumble
Which organizations are mentioning Kubeflow?
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