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ease
features
design
support

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Description

ML.NET is a versatile, open-source machine learning framework that is free to use and compatible across platforms, enabling .NET developers to create tailored machine learning models using C# or F# while remaining within the .NET environment. This framework encompasses a wide range of machine learning tasks such as classification, regression, clustering, anomaly detection, and recommendation systems. Additionally, ML.NET seamlessly integrates with other renowned machine learning frameworks like TensorFlow and ONNX, which broadens the possibilities for tasks like image classification and object detection. It comes equipped with user-friendly tools such as Model Builder and the ML.NET CLI, leveraging Automated Machine Learning (AutoML) to streamline the process of developing, training, and deploying effective models. These innovative tools automatically analyze various algorithms and parameters to identify the most efficient model for specific use cases. Moreover, ML.NET empowers developers to harness the power of machine learning without requiring extensive expertise in the field.

Description

Enhance your organization's machine learning capabilities through seamless management, deployment, and monitoring on a premier AI platform, all powered by navio. This tool enables the execution of a wide range of machine learning operations throughout your entire AI ecosystem. Transition your experiments from the lab to real-world applications, seamlessly incorporating machine learning into your operations for tangible business results. Navio supports you at every stage of the model development journey, from initial creation to deployment in a production environment. With automatic REST endpoint generation, you can easily monitor interactions with your model across different users and systems. Concentrate on exploring and fine-tuning your models to achieve optimal outcomes, while navio streamlines the setup of infrastructure and auxiliary features, saving you valuable time and resources. By allowing navio to manage the entire process of operationalizing your models, you can rapidly bring your machine learning innovations to market and start realizing their potential impact. This approach not only enhances efficiency but also boosts your organization's overall productivity in leveraging AI technologies.

API Access

Has API

API Access

Has API

Screenshots View All

Screenshots View All

Integrations

TensorFlow
.NET
Bing
C#
F#
Google Cloud AutoML
MLflow
Microsoft Azure
Microsoft Defender Antivirus
Microsoft Outlook
Microsoft Power BI
ONNX
Plotly Dash

Integrations

TensorFlow
.NET
Bing
C#
F#
Google Cloud AutoML
MLflow
Microsoft Azure
Microsoft Defender Antivirus
Microsoft Outlook
Microsoft Power BI
ONNX
Plotly Dash

Pricing Details

Free
Free Trial
Free Version

Pricing Details

No price information available.
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

Microsoft

Founded

1975

Country

United States

Website

dotnet.microsoft.com/en-us/apps/ai/ml-dotnet

Vendor Details

Company Name

craftworks GmbH

Country

Austria

Website

www.craftworks.ai/navio

Product Features

Machine Learning

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

Product 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)

Machine Learning

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

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