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What is ML.NET?

ML.NET is a flexible and open-source machine learning framework that is free and designed to work across various platforms, allowing .NET developers to build customized machine learning models utilizing C# or F# while staying within the .NET ecosystem. This framework supports an extensive array of machine learning applications, including classification, regression, clustering, anomaly detection, and recommendation systems. Furthermore, ML.NET offers seamless integration with other established machine learning frameworks such as TensorFlow and ONNX, enhancing the ability to perform advanced tasks like image classification and object detection. To facilitate user engagement, it provides intuitive tools such as Model Builder and the ML.NET CLI, which utilize Automated Machine Learning (AutoML) to simplify the development, training, and deployment of robust models. These cutting-edge tools automatically assess numerous algorithms and parameters to discover the most effective model for particular requirements. Additionally, ML.NET enables developers to tap into machine learning capabilities without needing deep expertise in the area, making it an accessible choice for many. This broadens the reach of machine learning, allowing more developers to innovate and create solutions that leverage data-driven insights.

What is Elham.ai?

Elham.ai is an intuitive no-code platform designed for machine learning, allowing users to effortlessly build and deploy AI models without needing any coding skills. The platform boasts an easy-to-navigate interface where users can upload their datasets and choose from various problem types, including classification and regression, while Elham handles crucial tasks such as data preprocessing, feature engineering, model training, evaluation, and deployment automatically. It also offers integration features via Zapier, which link to ChatGPT/OpenAI, enabling users to transform, summarize, or analyze their data using sophisticated AI models. Moreover, the sign-up and login processes are designed to be quick and straightforward, enabling teams to start leveraging the platform's capabilities without delay. By streamlining the machine-learning workflow, Elham.ai aims to convert raw data into valuable insights while efficiently managing the complexities associated with model tuning and infrastructure setup, thus significantly boosting user productivity. Furthermore, the platform's commitment to democratizing AI technology is evident, as it seeks to empower a wider range of users to harness the potential of artificial intelligence.

Media

Media

Integrations Supported

.NET
Bing
C#
ChatGPT
F#
Google Cloud AutoML
Microsoft Defender Antivirus
Microsoft Outlook
Microsoft Power BI
ONNX
OpenAI
TensorFlow
Zapier

Integrations Supported

.NET
Bing
C#
ChatGPT
F#
Google Cloud AutoML
Microsoft Defender Antivirus
Microsoft Outlook
Microsoft Power BI
ONNX
OpenAI
TensorFlow
Zapier

API Availability

Has API

API Availability

Has API

Pricing Information

Free
Free Trial Offered?
Free Version

Pricing Information

$559.75 per month
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

Microsoft

Date Founded

1975

Company Location

United States

Company Website

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

Company Facts

Organization Name

Elham.ai

Date Founded

2025

Company Location

Saudi Arabia

Company Website

elham.ai/

Categories and Features

Machine Learning

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

Categories and Features

Machine Learning

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

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