ML.NET

ML.NET

Microsoft
+
+

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About

Flower is an open source federated learning framework designed to simplify the development and deployment of machine learning models across decentralized data sources. It enables training on data located on devices or servers without transferring the data itself, thereby enhancing privacy and reducing bandwidth usage. Flower supports a wide range of machine learning frameworks, including PyTorch, TensorFlow, Hugging Face Transformers, scikit-learn, and XGBoost, and is compatible with various platforms and cloud services like AWS, GCP, and Azure. It offers flexibility through customizable strategies and supports both horizontal and vertical federated learning scenarios. Flower's architecture allows for scalable experiments, with the capability to handle workloads involving tens of millions of clients. It also provides built-in support for privacy-preserving techniques like differential privacy and secure aggregation.

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.

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

Machine learning practitioners and researchers in search of a tool to implement privacy-preserving, decentralized model training across diverse devices and platforms

Audience

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

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

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

Training

Documentation
Webinars
Live Online
In Person

Training

Documentation
Webinars
Live Online
In Person

Company Information

Flower
Founded: 2023
Germany
flower.ai/

Company Information

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

Alternatives

Alternatives

Keepsake

Keepsake

Replicate
AWS Neuron

AWS Neuron

Amazon Web Services
Apache Mahout

Apache Mahout

Apache Software Foundation

Categories

Categories

Integrations

TensorFlow
.NET
Android
Apple iOS
Bing
C#
F#
Google Cloud AutoML
Google Cloud Platform
Hugging Face
MXNet
Microsoft Defender Antivirus
Modern Leadership (MLX)
NVIDIA Jetson
NumPy
ONNX
PyTorch
Python
Raspberry Pi OS
scikit-learn

Integrations

TensorFlow
.NET
Android
Apple iOS
Bing
C#
F#
Google Cloud AutoML
Google Cloud Platform
Hugging Face
MXNet
Microsoft Defender Antivirus
Modern Leadership (MLX)
NVIDIA Jetson
NumPy
ONNX
PyTorch
Python
Raspberry Pi OS
scikit-learn
Claim Flower and update features and information
Claim Flower and update features and information
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