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features
design
support

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Description

Manage and optimize models throughout the entire ML lifecycle. This includes experiment tracking, monitoring production models, and more. The platform was designed to meet the demands of large enterprise teams that deploy ML at scale. It supports any deployment strategy, whether it is private cloud, hybrid, or on-premise servers. Add two lines of code into your notebook or script to start tracking your experiments. It works with any machine-learning library and for any task. To understand differences in model performance, you can easily compare code, hyperparameters and metrics. Monitor your models from training to production. You can get alerts when something is wrong and debug your model to fix it. You can increase productivity, collaboration, visibility, and visibility among data scientists, data science groups, and even business stakeholders.

Description

AI Cloud represents an innovative strategy designed to meet the current demands, challenges, and potential of artificial intelligence. This comprehensive system acts as a single source of truth, expediting the process of bringing AI solutions into production for organizations of all sizes. Users benefit from a collaborative environment tailored for ongoing enhancements throughout the entire AI lifecycle. The AI Catalog simplifies the process of discovering, sharing, tagging, and reusing data, which accelerates deployment and fosters teamwork. This catalog ensures that users can easily access relevant data to resolve business issues while maintaining high standards of security, compliance, and consistency. If your database is subject to a network policy restricting access to specific IP addresses, please reach out to Support for assistance in obtaining a list of IPs that should be added to your network policy for whitelisting, ensuring that your operations run smoothly. Additionally, leveraging AI Cloud can significantly improve your organization’s ability to innovate and adapt in a rapidly evolving technological landscape.

API Access

Has API Yes 

API Access

Has API No 

Screenshots View All

Screenshots View All

Integrations

Amazon SageMaker Yes 
Apache Spark Yes 
Clone Protocol Yes 
Flask Yes 
IBM Cloud Yes 
Ludwig Yes 
Lyftrondata No 
Membrane No 
Microsoft Azure Yes 
Mona No 
New Relic Yes 
Pipedream No 
Plotly Dash Yes 
Python Yes 
QlikMaps No 
Quickwork No 
TensorFlow Yes 
Ultralytics Yes 
UniverseBridge No 
ZenML Yes 

Integrations

Amazon SageMaker No 
Apache Spark No 
Clone Protocol No 
Flask No 
IBM Cloud No 
Ludwig No 
Lyftrondata Yes 
Membrane Yes 
Microsoft Azure No 
Mona Yes 
New Relic No 
Pipedream Yes 
Plotly Dash No 
Python No 
QlikMaps Yes 
Quickwork Yes 
TensorFlow No 
Ultralytics No 
UniverseBridge Yes 
ZenML No 

Pricing Details

$179 per user per month
Free Trial No 
Free Version Yes 

Pricing Details

No price information available.
Free Trial No 
Free Version No 

Deployment

Web-Based Yes 
On-Premises Yes 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Deployment

Web-Based Yes 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Customer Support

Business Hours No 
Live Rep (24/7) No 
Online Support Yes 

Customer Support

Business Hours No 
Live Rep (24/7) No 
Online Support Yes 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) Yes 
In Person No 

Types of Training

Training Docs Yes 
Webinars Yes 
Live Training (Online) No 
In Person No 

Vendor Details

Company Name

Comet

Founded

2017

Country

United States

Website

www.comet.com

Vendor Details

Company Name

DataRobot

Country

United States

Website

www.datarobot.com

Product Features

Data Science

Access Control No 
Advanced Modeling No 
Audit Logs No 
Data Discovery No 
Data Ingestion No 
Data Preparation No 
Data Visualization No 
Model Deployment No 
Reports No 

Deep Learning

Convolutional Neural Networks No 
Document Classification No 
Image Segmentation No 
ML Algorithm Library Yes 
Model Training Yes 
Neural Network Modeling No 
Self-Learning No 
Visualization Yes 

Machine Learning

Deep Learning Yes 
ML Algorithm Library Yes 
Model Training Yes 
Natural Language Processing (NLP) Yes 
Predictive Modeling No 
Statistical / Mathematical Tools No 
Templates No 
Visualization Yes 

Product Features

Data Science

Access Control No 
Advanced Modeling No 
Audit Logs No 
Data Discovery No 
Data Ingestion No 
Data Preparation No 
Data Visualization No 
Model Deployment No 
Reports No 

Deep Learning

Convolutional Neural Networks Yes 
Document Classification No 
Image Segmentation Yes 
ML Algorithm Library Yes 
Model Training Yes 
Neural Network Modeling Yes 
Self-Learning No 
Visualization Yes 

Machine Learning

Deep Learning Yes 
ML Algorithm Library Yes 
Model Training Yes 
Natural Language Processing (NLP) No 
Predictive Modeling Yes 
Statistical / Mathematical Tools No 
Templates Yes 
Visualization Yes 

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