This series gives an advanced guide to different recurrent neural networks (RNNs). You will gain an understanding of the networks themselves, their architectures, their applications, and how to bring the models to life using Keras.
In this article we'll dive into an in-depth discussion of a recently proposed attention mechanism, namely ECA-Net, published at CVPR 2020.
We cover basic mistakes that can lead to unnecessary copying of data and memory allocation in NumPy. We further cover NumPy internals, strides, reshaping, and transpose in detail.
This post will cover how testing is done for the coronavirus, why it's important in battling the pandemic, and how deep learning tools for medical imaging can help us improve the quality of COVID-19 testing.
In this article we cover how to train GauGAN on your own custom dataset. This is part of a series on Nvidia GauGANs.
