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DN2A
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DN2A

Overview
Synopsis

DN2A is a set of highly decoupled JavaScript modules for Neural Networks and Artificial Intelligence development. Each module is based on injection by configuration and you can use a single module alone, more of them together or just the complete set.

Category

Artificial Neural Network Software

Features

•Modularized components
•Configurable precision
•Configuration checker
•StepByStep training
•StepByGoal training
•Continuous training

License

Proprietary Software

Pricing

Subscription

Free Trial

Available

Users Size

Small (<50 employees), Medium (50 to 1000 employees), Enterprise (>1001 employees)

Company

DN2A

What is best?

•Modularized components
•Configurable precision
•Configuration checker
•StepByStep training
•StepByGoal training

PAT Rating™
Editor Rating
Aggregated User Rating
Rate Here
Ease of use
8.4
7.2
Features & Functionality
8.4
Advanced Features
8.6
Integration
8.5
Performance
8.6
Customer Support
7.4
Implementation
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Bottom Line

DN2A main goal is to allow you to design, train and use without pain Single Neural Networks as well as very powerful Neural Networks Chains through which implement your Artificial Intelligence solution.

8.3
Editor Rating
7.2
Aggregated User Rating
1 rating
You have rated this

DN2A is a set of highly decoupled JavaScript modules for Neural Networks and Artificial Intelligence development. Each module is based on injection by configuration.

Clients can use a single module alone, more of them together or just the complete set. DN2A’s main goal is to allow users to design, train and use Single Neural Networks with ease as well as very powerful Neural Networks Chains through which to implement their Artificial Intelligence solutions.

DN2A’s side goals are to simplify integration, to speed up training/querying, to allow clustering and to represent the architecture and the relative data of each Neural Network as a (re)combinable string strain that will be usable within genetics optimization techniques. Some of DN2A’s highlights include Modularized Components which aid the development and the clear separation of concerns with great benefits for those who want to use mixed solutions.

Configurable Precision helps to avoid the noise deriving from operation errors and default system precision limits with great improvement of the learning speed and performance stability.

Configuration Checker helps to write fewer details about configuration and to keep compatibility with older versions while the project evolves. StepByStep Training allows users to train neural networks doing a single iteration over the passed information without trying to reach a specific parametric condition.

StepByGoal Training enables users to train neural networks doing a finite or infinite number of iterations over the passed information unless a specific parametric condition is reached. Finally, Continuous Training helps to train neural networks doing an infinite number of iterations over the passed information.

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Ease of use
Features & Functionality
Advanced Features
Integration
Performance
Customer Support
Implementation
Renew & Recommend

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