Getting Started

In this library, we can customize many of our models, optimizers and others to fit our needs. This was made possible thanks to the object-orientated design of our library.

To start, we must first link our deep learning library with our tensor library. However, you must use “Aqwam’s Tensor Library” as every calculations made by our models are based on that tensor library.

Library Download Links

Deep Learning Library

Name	Release Version	Beta Version
Deep Learning Library (DataPredict Neural)	1.10	1.6.0

Tensor Library

Name	Version
Tensor Library (TensorL Nested)	0.9.0
Tensor Library - Efficient (TensorL Nested Efficient)	0.9.0
Tensor Library - Efficient (TensorL Nested Efficient Version 2)	0.9.0
Tensor Library - Efficient IPairs (TensorL Nested Efficient IPairs)	0.9.0
Tensor Library - Efficient IPairs (TensorL Nested Efficient IPairs Version 2)	0.9.0

Note: Tensor Library - Efficient IPairs Version 2 has the most consistent high performance for all tensor operations. So choose the last one if you prefer speed over code readability.

You can read the Terms And Conditions for the TensorL Library here.

Installing The Files Into Roblox Studio

To download the files from GitHub, you must click on the download button highlighted in the red box.

Then drag the files into Roblox Studio from a file explorer of your choice.

Once you put those two libraries into your game, make sure you link the Deep Learning Library with the Tensor Library. This can be done via setting the “AqwamTensorLibraryLinker” value (under the Deep Learning library) to the Tensor Library.

Next, we will use require() function to our deep learning library:

local DataPredictNeural = require(AqwamDeepLearningLibrary)