Computer Vision Paper Review: GhostNet (CVPR 2020) in PyTorch and TensorFlow In this post we'll take an in-depth look at feature maps in convolutional neural networks, do a thorough review of GhostNet, and break down the code in PyTorch and TensorFlow.
Keras A Guide to TensorFlow Callbacks TensorFlow callbacks are an essential part of training deep learning models, providing a high degree of control over many aspects of your model training.
Deep Learning Image Compression Using Autoencoders in Keras Autoencoders are a deep learning model for transforming data from a high-dimensional space to a lower-dimensional space. They work by encoding the data, whatever its size, to a 1-D vector.
Tutorial TensorFlow 2.0 in Action TensorFlow is one of the most popular frameworks used for deep learning projects and is approaching a major new release- Â TensorFlow 2.0. Luckily, we don't have to wait for
GAN Building a simple Generative Adversarial Network (GAN) using TensorFlow Generative Adversarial Networks or GANs are one of the most active areas in deep learning research and development due to their incredible ability to generate synthetic results. In this blog, we will build out the basic intuition of GANs through a concrete example.
