ML.NET

ML.NET

Microsoft
+
+

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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

Scikit-learn provides simple and efficient tools for predictive data analysis. Scikit-learn is a robust, open source machine learning library for the Python programming language, designed to provide simple and efficient tools for data analysis and modeling. Built on the foundations of popular scientific libraries like NumPy, SciPy, and Matplotlib, scikit-learn offers a wide range of supervised and unsupervised learning algorithms, making it an essential toolkit for data scientists, machine learning engineers, and researchers. The library is organized into a consistent and flexible framework, where various components can be combined and customized to suit specific needs. This modularity makes it easy for users to build complex pipelines, automate repetitive tasks, and integrate scikit-learn into larger machine-learning workflows. Additionally, the library’s emphasis on interoperability ensures that it works seamlessly with other Python libraries, facilitating smooth data processing.

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

Engineers and data scientists requiring a solution to manage and improve their machine learning research

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

Free
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

scikit-learn
United States
scikit-learn.org/stable/

Alternatives

Alternatives

Gensim

Gensim

Radim Řehůřek
ML.NET

ML.NET

Microsoft
AWS Neuron

AWS Neuron

Amazon Web Services
MLlib

MLlib

Apache Software Foundation
Apache Mahout

Apache Mahout

Apache Software Foundation
Keepsake

Keepsake

Replicate

Categories

Categories

Integrations

.NET
Bing
C#
DagsHub
Databricks
F#
GLM-5.1
Google Cloud AutoML
Keepsake
MLJAR Studio
Microsoft Defender Antivirus
Microsoft Outlook
Microsoft Power BI
ModelOp
NumPy
Python
TensorFlow
Thunder Compute
Train in Data

Integrations

.NET
Bing
C#
DagsHub
Databricks
F#
GLM-5.1
Google Cloud AutoML
Keepsake
MLJAR Studio
Microsoft Defender Antivirus
Microsoft Outlook
Microsoft Power BI
ModelOp
NumPy
Python
TensorFlow
Thunder Compute
Train in Data
Claim ML.NET and update features and information
Claim ML.NET and update features and information
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Claim scikit-learn and update features and information