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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 Kraken?

Kraken is tailored to meet the needs of a wide range of users, from analysts to data scientists. This intuitive, no-code automated machine learning platform simplifies the intricate world of data science. By streamlining critical processes such as data preparation, cleaning, algorithm selection, model training, and deployment, Kraken makes these tasks accessible to individuals across various skill levels. Analysts and engineers will particularly appreciate how their existing data analysis skills allow them to quickly adapt to using Kraken. The platform features a user-friendly interface and integrated SONAR© training, which enables users to transition into citizen data scientists with ease. For experienced data scientists, Kraken provides advanced functionalities that boost both speed and workflow efficiency. Whether your work involves Excel, flat files, or requires on-the-fly analyses, the easy drag-and-drop CSV upload and Amazon S3 integration make building models a breeze. Furthermore, Kraken’s Data Connectors allow for smooth integration with your favorite data warehouses, business intelligence platforms, and cloud storage services, creating a holistic data science environment. With Kraken, users of all experience levels can effortlessly tap into the capabilities of machine learning, fostering a collaborative and innovative atmosphere for all.

Media

Media

Integrations Supported

.NET
Bing
F#
Microsoft Defender Antivirus
Microsoft Outlook
Microsoft Power BI

Integrations Supported

Amazon S3
Domo
Google Cloud BigQuery
Kryptos
Looker
MySQL
Pulsar Finance
Qlik Sense
SQL Server
SimpleSwap
Snowflake
Tableau
Tradoshi

API Availability

API Availability

Pricing Information

Free
Free Version

Pricing Information

$100 per month
Free Trial Offered?

Supported Platforms

Windows
Mac
On-Prem
Linux

Supported Platforms

SaaS

Customer Service / Support

Standard Support
Web-Based Support

Customer Service / Support

Not specified

Training Options

Documentation Hub
Webinars
On-Site Training

Training Options

Not specified

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

Big Squid

Date Founded

2009

Company Location

United States

Company Website

www.bigsquid.com/kraken-platform

Categories and Features

AI/ML Model Training

Not specified

Machine Learning

Not specified

Categories and Features

AI/ML Model Training

Not specified

Big Data

Data Cleansing
Data Visualization
Predictive Analytics

Machine Learning

Deep Learning
ML Algorithm Library
Model Training
Predictive Modeling
Statistical / Mathematical Tools
Templates
Visualization

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