DeepNN
Deep Neural Net visualisation
Archived App (Last seen on 20 Feb 2025)
This is an archived listing of the app previously available on the App Store.Although the app is no longer distributed by Apple, you can still view its description, screenshots, version history, ratings, and metadata for reference.
About
Visualize the training process of a small Deep Neural Network directly on your iPhone or iPad. This app is designed purely for educational visualization purposes, offering a hands-on look at neural network mechanics.
What's New in DeepNN
1.5
June 17, 2019
many more hyper parameters to explore better Neural Network performance Learning Rate Finder (in Settings)
MoreDeveloper apps
FAQ
What is DeepNN used for?
DeepNN is used to observe a small Deep Neural Network train on your iPhone or iPad. It's purely for visualization purposes to help understand how neural networks learn.
Is DeepNN free to download?
Yes, DeepNN is available for free on the App Store. There are no costs associated with downloading or using the application.
What devices does DeepNN support?
DeepNN is compatible with iPhone, iPad, and iPod touch devices. It is designed to run on Apple's mobile operating system.
How often is DeepNN updated?
The latest version of DeepNN is 1.5, which was last updated on June 17, 2019. Updates are released by the developer Thomas Peter.
What is the age rating for DeepNN?
DeepNN has an age rating of 4+. This indicates it is suitable for a wide range of users, including younger learners.
Does DeepNN have ads?
No, DeepNN does not contain advertisements. The app is ad-free, providing an uninterrupted visualization experience.
Can I train my own neural networks with DeepNN?
DeepNN is designed for visualization purposes, allowing you to observe a pre-defined small Deep Neural Network train. It does not currently support training custom networks.
What learning methodology does DeepNN employ?
DeepNN employs a visual learning methodology. By observing the training process of a neural network in real-time, users can gain a concrete understanding of abstract concepts.
