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features
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support

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Description

Azure Machine Learning Studio enables organizations to streamline the entire machine learning lifecycle from start to finish. Equip developers and data scientists with an extensive array of efficient tools for swiftly building, training, and deploying machine learning models. Enhance the speed of market readiness and promote collaboration among teams through leading-edge MLOps—akin to DevOps but tailored for machine learning. Drive innovation within a secure, reliable platform that prioritizes responsible AI practices. Cater to users of all expertise levels with options for both code-centric and drag-and-drop interfaces, along with automated machine learning features. Implement comprehensive MLOps functionalities that seamlessly align with existing DevOps workflows, facilitating the management of the entire machine learning lifecycle. Emphasize responsible AI by providing insights into model interpretability and fairness, securing data through differential privacy and confidential computing, and maintaining control over the machine learning lifecycle with audit trails and datasheets. Additionally, ensure exceptional compatibility with top open-source frameworks and programming languages such as MLflow, Kubeflow, ONNX, PyTorch, TensorFlow, Python, and R, thus broadening accessibility and usability for diverse projects. By fostering an environment that promotes collaboration and innovation, teams can achieve remarkable advancements in their machine learning endeavors.

Description

Integrate AI seamlessly into your business to enhance trust and efficiency. Accelerate development and streamline deployment with the advantages of a cloud-native platform that allows for versatile deployment options. Effortlessly import models and access a well-organized model catalog from various departments within your organization. Save valuable time by quickly annotating data through model-in-the-loop hinting. Gain comprehensive insights into the origins and history of your data, models, workflows, and inferences, ensuring transparency at every step. Deploy models precisely where needed, including in edge and IoT scenarios, bridging gaps between technology and real-world applications. Valuable insights can be harnessed by all team members, not just data scientists, thanks to Chariot’s intuitive low-code interface that fosters collaboration across different teams. Rapidly train models using your organization’s production data and benefit from the convenience of one-click deployment, all while maintaining the ability to monitor model performance at scale to ensure ongoing efficacy. This comprehensive approach not only improves operational efficiency but also empowers teams to make informed decisions based on data-driven insights.

API Access

Has API No 

API Access

Has API Yes 

Screenshots View All

Screenshots View All

Integrations

Azure AI Search Yes 
Azure Container Registry Yes 
Azure Data Science Virtual Machines Yes 
Azure Database for MariaDB Yes 
Azure Kinect DK Yes 
Azure Percept Yes 
BotCore Yes 
Cranium Yes 
Evvox Yes 
Kedro Yes 
MLflow Yes 
Microsoft Intelligent Data Platform Yes 
ModelOp Yes 
NVIDIA Triton Inference Server Yes 
New Relic Yes 
Omnisient Yes 
Slingshot Yes 
Superwise Yes 
Visual Studio Code Yes 
Wizata Yes 

Integrations

Azure AI Search No 
Azure Container Registry No 
Azure Data Science Virtual Machines No 
Azure Database for MariaDB No 
Azure Kinect DK No 
Azure Percept No 
BotCore No 
Cranium No 
Evvox No 
Kedro No 
MLflow No 
Microsoft Intelligent Data Platform No 
ModelOp No 
NVIDIA Triton Inference Server No 
New Relic No 
Omnisient No 
Slingshot No 
Superwise No 
Visual Studio Code No 
Wizata No 

Pricing Details

No price information available.
Free Trial Yes 
Free Version No 

Pricing Details

No price information available.
Free Trial No 
Free Version 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 

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) No 
In Person No 

Types of Training

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

Vendor Details

Company Name

Microsoft

Founded

1975

Country

United States

Website

azure.microsoft.com/en-us/products/machine-learning/

Vendor Details

Company Name

Striveworks

Founded

2018

Country

United States

Website

www.striveworks.com/platform

Product Features

Data Labeling

Human-in-the-loop Yes 
Labeling Automation Yes 
Labeling Quality Yes 
Performance Tracking Yes 
Polygon, Rectangle, Line, Point Yes 
SDK Yes 
Supports Audio Files Yes 
Task Management Yes 
Team Collaboration Yes 
Training Data Management Yes 

Machine Learning

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

Product Features

Machine Learning

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

Alternatives

Alternatives