HPE Ezmeral ML OPS

HPE Ezmeral ML OPS

HPE Ezmeral ML Ops offers a suite of pre-packaged tools designed to streamline machine learning workflows throughout the entire lifecycle, from pilot to production. Users can quickly create environments tailored to their preferred data science tools, experiment with various machine learning frameworks, and securely access enterprise data sources across on-premises or cloud storage. With self-service capabilities, it supports development, testing, and production workloads, while enabling source control through integrated tools like GitHub. Additionally, it features a model registry that stores multiple versions of models along with their metadata for various runtime engines.

Top HPE Ezmeral ML OPS Alternatives

1

Hugging Face

This innovative platform empowers the machine learning community to create, share, and collaborate on models, datasets, and applications.

2

Azure Notebooks

Azure Notebooks offers an intuitive platform for developing and running code in Jupyter notebooks via any web browser.

3

Protege

Protégé is a powerful, Java-based platform widely utilized across academia, government, and corporate sectors to develop knowledge-based applications.

4

Kubeflow

Kubeflow facilitates the deployment and management of machine learning workflows on Kubernetes.

5

Oracle Data Science

This data science platform enhances productivity by enabling users to build and evaluate superior machine learning models efficiently.

6

MLflow

MLflow 2.0 revolutionizes machine learning workflows by integrating user feedback to enhance data science processes.

7

AWS Elastic Fabric Adapter (EFA)

With its custom OS bypass mechanism, EFA significantly boosts performance for HPC and machine learning...

8

Splunk Machine Learning Toolkit

It offers over 300 open-source algorithms, custom SPL commands, and guided Assistants for model building...

9

Amazon SageMaker Model Training

It features advanced distributed training libraries, enabling efficient data handling across AWS instances...

10

Altair Knowledge Works

With its low-code, cloud-ready interface, data scientists and analysts can efficiently operationalize applications...

11

Amazon SageMaker Model Monitor

It allows users to monitor data and model quality effortlessly, utilizing built-in statistical rules to...

12

H2O.ai

With scalable Kubernetes support, customizable AI models, and robust guardrails for compliance, users can create...

13

Amazon SageMaker Model Deployment

It supports low-latency and high-throughput scenarios, integrates seamlessly with MLOps tools, and automates model scaling...

14

neptune.ai

It enables teams to monitor per-layer performance, quickly identifying issues like vanishing gradients...

15

Amazon SageMaker Model Building

It integrates diverse tools for data preparation, model training, and deployment, enhancing collaboration with AI-powered...