Average Ratings 0 Ratings
Average Ratings 0 Ratings
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
Microsoft is actively advancing its R-related offerings, evident not only in the latest release of Machine Learning Server but also in the newest versions of Microsoft R Client and Microsoft R Open. Furthermore, R and Python integration is available within SQL Server Machine Learning Services for both Windows and Linux platforms, alongside R support in Azure SQL Database. The R components maintain backward compatibility, allowing users to execute existing R scripts on newer versions, as long as they do not rely on outdated packages or platforms that are no longer supported, or on known problems that necessitate workarounds or code modifications. Microsoft R Open serves as the enhanced version of R provided by Microsoft Corporation, with the most recent release, Microsoft R Open 4.0.2, built on the statistical language R-4.0.2, offering additional features for better performance, reproducibility, and platform compatibility. This version ensures compatibility with all packages, scripts, and applications built on R-4.0.2, making it a reliable choice for developers and data scientists alike. Overall, Microsoft's dedication to R fosters an environment of continuous improvement and support for its users.
API Access
Has API
Yes
API Access
Has API
No
Integrations
Amazon SageMaker
Yes
Amazon Web Services (AWS)
Yes
Apache Spark
Yes
Azure HDInsight
No
Clone Protocol
Yes
DataClarity Unlimited Analytics
No
Delinea Cloud Access Controller
No
Flask
Yes
Juniper Identity Management Service
No
Keras
Yes
Integrations
Amazon SageMaker
No
Amazon Web Services (AWS)
No
Apache Spark
No
Azure HDInsight
Yes
Clone Protocol
No
DataClarity Unlimited Analytics
Yes
Delinea Cloud Access Controller
Yes
Flask
No
Juniper Identity Management Service
Yes
Keras
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
Yes
Mac
Yes
Linux
Yes
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
No
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
Microsoft
Founded
1975
Country
United States
Website
mran.microsoft.com/rro
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