ML.NET

ML.NET

Microsoft
Weka

Weka

University of Waikato
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+

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About

ML.NET is a free, open source, and cross-platform machine learning framework designed for .NET developers to build custom machine learning models using C# or F# without leaving the .NET ecosystem. It supports various machine learning tasks, including classification, regression, clustering, anomaly detection, and recommendation systems. ML.NET integrates with other popular ML frameworks like TensorFlow and ONNX, enabling additional scenarios such as image classification and object detection. It offers tools like Model Builder and the ML.NET CLI, which utilize Automated Machine Learning (AutoML) to simplify the process of building, training, and deploying high-quality models. These tools automatically explore different algorithms and settings to find the best-performing model for a given scenario.

About

Weka is a collection of machine learning algorithms for data mining tasks. It contains tools for data preparation, classification, regression, clustering, association rules mining, and visualization. Found only on the islands of New Zealand, the Weka is a flightless bird with an inquisitive nature. The name is pronounced like this, and the bird sounds like this. Weka is open source software issued under the GNU General Public License. We have put together several free online courses that teach machine learning and data mining using Weka. The videos for the courses are available on Youtube. An exciting and potentially far-reaching development in computer science is the invention and application of methods of machine learning (ML). These enable a computer program to automatically analyze a large body of data and decide what information is most relevant. This crystallized information can then be used to automatically make predictions or to help people make decisions faster.

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Audience

.NET developers searching for a tool to incorporate machine learning capabilities into their applications using familiar languages and tools

Audience

Companies, researchers and organizations in need of a machine learning solution for their projects

Support

Phone Support
24/7 Live Support
Online

Support

Phone Support
24/7 Live Support
Online

API

Offers API

API

Offers API

Screenshots and Videos

Screenshots and Videos

Pricing

Free
Free Version
Free Trial

Pricing

No information available.
Free Version
Free Trial

Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

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Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

This software hasn't been reviewed yet. Be the first to provide a review:

Review this Software

Training

Documentation
Webinars
Live Online
In Person

Training

Documentation
Webinars
Live Online
In Person

Company Information

Microsoft
Founded: 1975
United States
dotnet.microsoft.com/en-us/apps/ai/ml-dotnet

Company Information

University of Waikato
New Zealand
www.cs.waikato.ac.nz/ml/weka/

Alternatives

Alternatives

Neural Designer

Neural Designer

Artelnics
RapidMiner

RapidMiner

Altair
Vertex AI

Vertex AI

Google
AWS Neuron

AWS Neuron

Amazon Web Services
Apache Mahout

Apache Mahout

Apache Software Foundation
Apache Mahout

Apache Mahout

Apache Software Foundation

Categories

Categories

Machine Learning Features

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

Integrations

.NET
AWS Marketplace
Bing
C#
F#
Google Cloud AutoML
Microsoft Defender Antivirus
Microsoft Outlook
Microsoft Power BI
ONNX
TensorFlow

Integrations

.NET
AWS Marketplace
Bing
C#
F#
Google Cloud AutoML
Microsoft Defender Antivirus
Microsoft Outlook
Microsoft Power BI
ONNX
TensorFlow
Claim ML.NET and update features and information
Claim ML.NET and update features and information
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Claim Weka and update features and information