Example code for using Tensorflow 2.0 with both numerical and categorical data
-
Updated
Oct 5, 2021 - Python
Example code for using Tensorflow 2.0 with both numerical and categorical data
This is a Tensorflow implementation of text recognition model from the paper "An End-to-End Trainable Neural Network for Image-based Sequence Recognition and Its Application to Scene Text Recognition".
MobileNetV2 written in tensorflow, training with eager mode and estimator API
Image Style Transfer in TensorFlow
Major GANs are implemented in this repository 🔥
Major anomaly detection methods using neural networks are implemented in this repository 🔥
3 different ways to implement GD in TF2.0
Foolbox Native brings native performance to Foolbox
Tensor utilities, reinforcement learning, and more!
Eagerly Experimentable!!!
An example of semantic segmentation using tensorflow in eager execution.
Cyclic learning rate TensorFlow implementation.
TensorFlow implementation of DropBlock
TensorFlow implementation of Deformable Convolutional Layer
A Tensorflow Keras implementation (Graph and eager execution) of Mnasnet: MnasNet: Platform-Aware Neural Architecture Search for Mobile.
TensorFlow Eager implementation of NEAT and Adaptive HyperNEAT
Tensorflow implementation of Ordinary Differential Equation Solvers with full GPU support
PyTorch, TensorFlow, JAX and NumPy — all of them natively using the same code
Add a description, image, and links to the eager-execution topic page so that developers can more easily learn about it.
To associate your repository with the eager-execution topic, visit your repo's landing page and select "manage topics."