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

A data science platform that improves productivity with unparalleled abilities. Build and evaluate higher-quality machine learning (ML) models. Increase business flexibility by putting enterprise-trusted data to work quickly and support data-driven business objectives with easier deployment of ML models. Using cloud-based platforms to discover new business insights. Building a machine learning model is an iterative process. In this ebook, we break down the process and describe how machine learning models are built. Explore notebooks and build or test machine learning algorithms. Try AutoML and see data science results. Build high-quality models faster and easier. Automated machine learning capabilities rapidly examine the data and recommend the optimal data features and best algorithms. Additionally, automated machine learning tunes the model and explains the model’s results.

About

An end-to-end open source machine learning platform. TensorFlow is an end-to-end open source platform for machine learning. It has a comprehensive, flexible ecosystem of tools, libraries and community resources that lets researchers push the state-of-the-art in ML and developers easily build and deploy ML powered applications. Build and train ML models easily using intuitive high-level APIs like Keras with eager execution, which makes for immediate model iteration and easy debugging. Easily train and deploy models in the cloud, on-prem, in the browser, or on-device no matter what language you use. A simple and flexible architecture to take new ideas from concept to code, to state-of-the-art models, and to publication faster. Build, deploy, and experiment easily with TensorFlow.

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

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 searching for a data science platform that improves productivity

Audience

Organizations interested in a powerful open source machine learning platform

Support

Phone Support
24/7 Live Support
Online

Support

Phone Support
24/7 Live Support
Online

Support

Phone Support
24/7 Live Support
Online

API

Offers API

API

Offers API

API

Offers API

Screenshots and Videos

Screenshots and Videos

Screenshots and Videos

Pricing

Free
Free Version
Free Trial

Pricing

No information available.
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

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

Review this Software

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

Reviews/Ratings

Overall 5.0 / 5
ease 5.0 / 5
features 5.0 / 5
design 5.0 / 5
support 5.0 / 5

Training

Documentation
Webinars
Live Online
In Person

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

Oracle
Founded: 1977
United States
www.oracle.com/data-science/

Company Information

TensorFlow
Founded: 2015
United States
www.tensorflow.org

Alternatives

Alternatives

Alternatives

Vertex AI

Vertex AI

Google
AWS Neuron

AWS Neuron

Amazon Web Services
Apache Mahout

Apache Mahout

Apache Software Foundation
TensorBoard

TensorBoard

Tensorflow

Categories

Categories

Categories

Machine Learning Features

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

Integrations

AUSIS
Amazon EC2 P5 Instances
Amazon SageMaker Debugger
Dragonfly 3D World
Fabric for Deep Learning (FfDL)
GitSummarize
IREN Cloud
JAX
Jupyter Notebook
Keras
LaunchX
Lightly
Microsoft Outlook
OCI Data Labeling
Radicalbit
Tecton
TensorBoard
TensorWave
Unify AI

Integrations

AUSIS
Amazon EC2 P5 Instances
Amazon SageMaker Debugger
Dragonfly 3D World
Fabric for Deep Learning (FfDL)
GitSummarize
IREN Cloud
JAX
Jupyter Notebook
Keras
LaunchX
Lightly
Microsoft Outlook
OCI Data Labeling
Radicalbit
Tecton
TensorBoard
TensorWave
Unify AI

Integrations

AUSIS
Amazon EC2 P5 Instances
Amazon SageMaker Debugger
Dragonfly 3D World
Fabric for Deep Learning (FfDL)
GitSummarize
IREN Cloud
JAX
Jupyter Notebook
Keras
LaunchX
Lightly
Microsoft Outlook
OCI Data Labeling
Radicalbit
Tecton
TensorBoard
TensorWave
Unify AI
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