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Average Ratings 0 Ratings

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ease
features
design
support

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Description

HPE Ezmeral ML Ops offers a suite of integrated tools designed to streamline machine learning workflows throughout the entire ML lifecycle, from initial pilot stages to full production, ensuring rapid and agile operations akin to DevOps methodologies. You can effortlessly set up environments using your choice of data science tools, allowing you to delve into diverse enterprise data sources while simultaneously testing various machine learning and deep learning frameworks to identify the most suitable model for your specific business challenges. The platform provides self-service, on-demand environments tailored for both development and production tasks. Additionally, it features high-performance training environments that maintain a clear separation between compute and storage, enabling secure access to shared enterprise data, whether it resides on-premises or in the cloud. Moreover, HPE Ezmeral ML Ops supports source control through seamless integration with popular tools like GitHub. You can manage numerous model versions—complete with metadata—within the model registry, facilitating better organization and retrieval of your machine learning assets. This comprehensive approach not only optimizes workflow management but also enhances collaboration among teams.

Description

Neptune.ai serves as a robust platform for machine learning operations (MLOps), aimed at simplifying the management of experiment tracking, organization, and sharing within the model-building process. It offers a thorough environment for data scientists and machine learning engineers to log data, visualize outcomes, and compare various model training sessions, datasets, hyperparameters, and performance metrics in real-time. Seamlessly integrating with widely-used machine learning libraries, Neptune.ai allows teams to effectively oversee both their research and production processes. Its features promote collaboration, version control, and reproducibility of experiments, ultimately boosting productivity and ensuring that machine learning initiatives are transparent and thoroughly documented throughout their entire lifecycle. This platform not only enhances team efficiency but also provides a structured approach to managing complex machine learning workflows.

API Access

Has API

API Access

Has API

Screenshots View All

Screenshots View All

Integrations

Amazon SageMaker
Arize AI
Bokeh
Deepnote
Google Colab
HPE Ezmeral
Jupyter Notebook
JupyterLab
Keras
MLflow
Plotly Dash
PyTorch
TensorFlow

Integrations

Amazon SageMaker
Arize AI
Bokeh
Deepnote
Google Colab
HPE Ezmeral
Jupyter Notebook
JupyterLab
Keras
MLflow
Plotly Dash
PyTorch
TensorFlow

Pricing Details

No price information available.
Free Trial
Free Version

Pricing Details

$49 per month
Free Trial
Free Version

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Vendor Details

Company Name

Hewlett Packard Enterprise

Founded

2015

Country

United States

Website

www.hpe.com/us/en/solutions/ezmeral-machine-learning-operations.html

Vendor Details

Company Name

neptune.ai

Founded

2017

Country

United States

Website

neptune.ai/

Product Features

Machine Learning

Deep Learning
ML Algorithm Library
Model Training
Natural Language Processing (NLP)
Predictive Modeling
Statistical / Mathematical Tools
Templates
Visualization

Product Features

Machine Learning

Deep Learning
ML Algorithm Library
Model Training
Natural Language Processing (NLP)
Predictive Modeling
Statistical / Mathematical Tools
Templates
Visualization

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