Ratings and Reviews 0 Ratings

Total
ease
features
design
support

This software has no reviews. Be the first to write a review.

Write a Review

Ratings and Reviews 0 Ratings

Total
ease
features
design
support

This software has no reviews. Be the first to write a review.

Write a Review

Alternatives to Consider

  • Vertex AI Reviews & Ratings
    783 Ratings
    Company Website
  • RunPod Reviews & Ratings
    180 Ratings
    Company Website
  • Fraud.net Reviews & Ratings
    56 Ratings
    Company Website
  • Teradata VantageCloud Reviews & Ratings
    992 Ratings
    Company Website
  • Cloudflare Reviews & Ratings
    1,903 Ratings
    Company Website
  • Bitrise Reviews & Ratings
    385 Ratings
    Company Website
  • Google AI Studio Reviews & Ratings
    10 Ratings
    Company Website
  • Google Cloud Speech-to-Text Reviews & Ratings
    373 Ratings
    Company Website
  • Google Cloud BigQuery Reviews & Ratings
    1,927 Ratings
    Company Website
  • Guardz Reviews & Ratings
    103 Ratings
    Company Website

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 Kubeflow?

The Kubeflow project is designed to streamline the deployment of machine learning workflows on Kubernetes, making them both scalable and easily portable. Instead of replicating existing services, we concentrate on providing a user-friendly platform for deploying leading open-source ML frameworks across diverse infrastructures. Kubeflow is built to function effortlessly in any environment that supports Kubernetes. One of its standout features is a dedicated operator for TensorFlow training jobs, which greatly enhances the training of machine learning models, especially in handling distributed TensorFlow tasks. Users have the flexibility to adjust the training controller to leverage either CPUs or GPUs, catering to various cluster setups. Furthermore, Kubeflow enables users to create and manage interactive Jupyter notebooks, which allows for customized deployments and resource management tailored to specific data science projects. Before moving workflows to a cloud setting, users can test and refine their processes locally, ensuring a smoother transition. This adaptability not only speeds up the iteration process for data scientists but also guarantees that the models developed are both resilient and production-ready, ultimately enhancing the overall efficiency of machine learning projects. Additionally, the integration of these features into a single platform significantly reduces the complexity associated with managing multiple tools.

Media

Media

Integrations Supported

.NET
APERIO DataWise
Azure Marketplace
Bing
C#
Civo
D2iQ
F#
Flyte
Giskard
Google Cloud AutoML
Kubernetes
Microsoft Outlook
ONNX
PredictKube
Robust Intelligence
Superwise
TensorFlow
Unremot
ZenML

Integrations Supported

.NET
APERIO DataWise
Azure Marketplace
Bing
C#
Civo
D2iQ
F#
Flyte
Giskard
Google Cloud AutoML
Kubernetes
Microsoft Outlook
ONNX
PredictKube
Robust Intelligence
Superwise
TensorFlow
Unremot
ZenML

API Availability

Has API

API Availability

Has API

Pricing Information

Free
Free Trial Offered?
Free Version

Pricing Information

Pricing not provided.
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

Kubeflow

Company Website

www.kubeflow.org

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

Popular Alternatives

Popular Alternatives

Vertex AI Reviews & Ratings

Vertex AI

Google
Union Cloud Reviews & Ratings

Union Cloud

Union.ai
AWS Neuron Reviews & Ratings

AWS Neuron

Amazon Web Services