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features
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support

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Description

ML.NET is a versatile, open-source machine learning framework that is free to use and compatible across platforms, enabling .NET developers to create tailored machine learning models using C# or F# while remaining within the .NET environment. This framework encompasses a wide range of machine learning tasks such as classification, regression, clustering, anomaly detection, and recommendation systems. Additionally, ML.NET seamlessly integrates with other renowned machine learning frameworks like TensorFlow and ONNX, which broadens the possibilities for tasks like image classification and object detection. It comes equipped with user-friendly tools such as Model Builder and the ML.NET CLI, leveraging Automated Machine Learning (AutoML) to streamline the process of developing, training, and deploying effective models. These innovative tools automatically analyze various algorithms and parameters to identify the most efficient model for specific use cases. Moreover, ML.NET empowers developers to harness the power of machine learning without requiring extensive expertise in the field.

Description

Effortlessly link your data to the engine by either uploading a file or establishing a connection to a database. Once connected, you can begin to explore your data through various visualizations, or you can prepare it for machine learning modeling using data wrangling techniques and reusable recipes. Maximize the potential of your data by constructing machine learning models with regression, classification, or clustering algorithms—all without requiring any coding skills. Discover valuable insights into your dataset through tools that highlight feature importance, explain predictions, and allow for scenario analysis. Additionally, you can make forecasts and easily integrate them into your current systems using our pre-configured connectors, enabling you to take immediate action based on your findings. This streamlined process empowers you to unlock the full value of your data and drive informed decision-making.

API Access

Has API No 

API Access

Has API Yes 

Screenshots View All

Screenshots View All

Integrations

Microsoft Power BI Yes 
.NET Yes 
Apache Parquet No 
Bing Yes 
C# Yes 
F# Yes 
Google Cloud AutoML Yes 
Google Sheets No 
InterSystems IRIS No 
JSON No 
Microsoft Defender Antivirus Yes 
Microsoft Excel No 
Microsoft Outlook Yes 
MongoDB No 
ONNX Yes 
Oracle Database No 
PostgreSQL No 
SQL Server No 
Snowflake No 
TensorFlow Yes 

Integrations

Microsoft Power BI Yes 
.NET No 
Apache Parquet Yes 
Bing No 
C# No 
F# No 
Google Cloud AutoML No 
Google Sheets Yes 
InterSystems IRIS Yes 
JSON Yes 
Microsoft Defender Antivirus No 
Microsoft Excel Yes 
Microsoft Outlook No 
MongoDB Yes 
ONNX No 
Oracle Database Yes 
PostgreSQL Yes 
SQL Server Yes 
Snowflake Yes 
TensorFlow No 

Pricing Details

Free
Free Trial No 
Free Version Yes 

Pricing Details

$39 per month
Free Trial Yes 
Free Version No 

Deployment

Web-Based No 
On-Premises Yes 
iPhone App No 
iPad App No 
Android App No 
Windows Yes 
Mac Yes 
Linux Yes 
Chromebook No 

Deployment

Web-Based Yes 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Customer Support

Business Hours Yes 
Live Rep (24/7) No 
Online Support Yes 

Customer Support

Business Hours No 
Live Rep (24/7) No 
Online Support Yes 

Types of Training

Training Docs Yes 
Webinars Yes 
Live Training (Online) No 
In Person Yes 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) No 
In Person No 

Vendor Details

Company Name

Microsoft

Founded

1975

Country

United States

Website

dotnet.microsoft.com/en-us/apps/ai/ml-dotnet

Vendor Details

Company Name

PI.EXCHANGE

Founded

2017

Country

Australia

Website

www.pi.exchange/the-ai-and-analytics-engine

Product Features

Machine Learning

Deep Learning No 
ML Algorithm Library No 
Model Training No 
Natural Language Processing (NLP) No 
Predictive Modeling No 
Statistical / Mathematical Tools No 
Templates No 
Visualization No 

Product Features

Data Preparation

Collaboration Tools No 
Data Access No 
Data Blending No 
Data Cleansing No 
Data Governance No 
Data Mashup No 
Data Modeling No 
Data Transformation No 
Machine Learning No 
Visual User Interface No 

Machine Learning

Deep Learning No 
ML Algorithm Library No 
Model Training No 
Natural Language Processing (NLP) No 
Predictive Modeling No 
Statistical / Mathematical Tools No 
Templates No 
Visualization No 

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