Welcome to Aqwam’s DataPredict™ Axon Library!
By using or possessing any copies of this library or its assets (including the icons), you agree to our Terms And Conditions. In short:
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Public attribution is required when using this library.
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A separate agreement is needed for commercial use (both internally and externally). This applies to companies (or individuals, if none) whose combined revenue (including from subsidiaries or related entities) exceeds $3,000 within 365 days (not per 365 days) or those engaged in business-to-business activities.
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If you or your company is applicable to the above statement and do not want a separate agreement, then you are required to follow the “Commercial Use Conditions” in Terms And Conditions.
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Plus some more stuff…
Once you pass the commercial use threshold and want to license it, expect to pay for 2% of your project’s generated revenue, provided that it uses this library. All the money will be used for future research and improvements that will be released to the public.
It requires near PhD-level knowledge to build and test all the models in this library. To all indie devs who just starting their business, feel free to use it without burning away your money!
For information regarding potential license violations and eligibility for a bounty reward, please refer to the Terms And Conditions Violation Bounty Reward Information.
Version | Current Version Number |
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Release | 1.1 |
Beta | 0.1.0 |
DataPredict™ Axon is an advanced deep learning library for Roblox and Pure Lua.
This project is created as a direct upgrade to the DataPredict™ Neural library.
If there are any suggestions or issues for this library, don’t be afraid to reach out to me at my Discord server, DevForum thread or my LinkedIn.
In addition, if you are interested in Roblox tutorials and future projects by me, then you can subscribe to me in YouTube.
Tutorials
Installation
The Model Basics
Creating Our First Neural Network
Saving And Loading Model Weights
The Tensor Basics
Spatial Dimension Kernel And Stride
The Advanced Layers
Using Pooling Layers And Convolution Layers