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What is PwC Model Edge?

Model Edge facilitates the entire lifecycle management of models by streamlining the development, validation, governance, and oversight of your full portfolio, encompassing AI functionalities through a singular platform. This efficient operation bolsters your confidence in the program by providing vital tools that highlight the effectiveness and explainability of models to both internal teams and external partners. The platform is equipped with comprehensive model recording and documentation features, all housed within a cohesive environment. Furthermore, it presents a detailed inventory of models along with an audit trail that records historical and real-time changes and updates. By employing a centralized cloud-based system, you can manage every stage of a model’s lifecycle, from its initial idea to complete deployment. This enables you to effectively orchestrate workflows for model development and validation while keeping track of progress across different initiatives, ensuring every step is meticulously monitored and optimized. Such an all-encompassing strategy not only promotes enhanced collaboration but also significantly improves accountability throughout the model management framework, making it an indispensable tool for organizations. Ultimately, Model Edge stands as a pivotal resource that empowers organizations to harness the full potential of their modeling capabilities.

What is Azure Machine Learning?

Optimize the complete machine learning process from inception to execution. Empower developers and data scientists with a variety of efficient tools to quickly build, train, and deploy machine learning models. Accelerate time-to-market and improve team collaboration through superior MLOps that function similarly to DevOps but focus specifically on machine learning. Encourage innovation on a secure platform that emphasizes responsible machine learning principles. Address the needs of all experience levels by providing both code-centric methods and intuitive drag-and-drop interfaces, in addition to automated machine learning solutions. Utilize robust MLOps features that integrate smoothly with existing DevOps practices, ensuring a comprehensive management of the entire ML lifecycle. Promote responsible practices by guaranteeing model interpretability and fairness, protecting data with differential privacy and confidential computing, while also maintaining a structured oversight of the ML lifecycle through audit trails and datasheets. Moreover, extend exceptional support for a wide range of open-source frameworks and programming languages, such as MLflow, Kubeflow, ONNX, PyTorch, TensorFlow, Python, and R, facilitating the adoption of best practices in machine learning initiatives. By harnessing these capabilities, organizations can significantly boost their operational efficiency and foster innovation more effectively. This not only enhances productivity but also ensures that teams can navigate the complexities of machine learning with confidence.

Media

Media

Integrations Supported

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

Integrations Supported

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

API Availability

Has API

API Availability

Has API

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Company Facts

Organization Name

PwC

Date Founded

1998

Company Location

United Kingdom

Company Website

www.pwc.com/us/en/products/model-edge.html

Company Facts

Organization Name

Microsoft

Date Founded

1975

Company Location

United States

Company Website

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

Categories and Features

Artificial Intelligence

Chatbot
For Healthcare
For Sales
For eCommerce
Image Recognition
Machine Learning
Multi-Language
Natural Language Processing
Predictive Analytics
Process/Workflow Automation
Rules-Based Automation
Virtual Personal Assistant (VPA)

Categories and Features

Data Labeling

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

Machine Learning

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

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