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 # py/cuTAGI Documentation
 
-> cuTAGI is an open-source Bayesian neural networks library that is based on Tractable Approximate Gaussian Inference (TAGI) theory. It supports various neural network architectures such as full-connected, convolutional, and transpose convolutional layers, as well as skip connections, pooling and normalization layers. cuTAGI is capable of performing different tasks such as supervised, unsupervised, and reinforcement learning. This library has a python API called pyTAGI that allows users to easily use the C++ and CUDA libraries.
+cuTAGI is an open-source Bayesian neural networks library that is based on Tractable Approximate Gaussian Inference (TAGI) theory. It supports various neural network architectures such as full-connected, convolutional, and transpose convolutional layers, as well as skip connections, pooling and normalization layers. cuTAGI is capable of performing different tasks such as supervised, unsupervised, and reinforcement learning. This library has a python API called pyTAGI that allows users to easily use the C++ and CUDA libraries.
 
 
 ## Getting Started