Lightweight Python package for automatic differentiation
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Updated
May 19, 2024 - C++
Lightweight Python package for automatic differentiation
Major anomaly detection methods using neural networks are implemented in this repository 🔥
Image Style Transfer in TensorFlow
meachine learning
Get started with Tensorflow/Keras API.
This repository contains Various Techniques that can be used for object detection.
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".
A modular C++17 framework for automatic differentiation
Using an RNN to make predictions about redactions from the Mueller report
Major GANs are implemented in this repository 🔥
نقل النمط العصبوني: بناء طريقة للتعلم العميق باستخدام كيراس tf.keras و منفّذ إيجر eager execution
Simple Examples with TensorFlow from scratch
3 different ways to implement GD in TF2.0
MobileNetV2 written in tensorflow, training with eager mode and estimator API
Header only lazy evaluation tensor math library with multi-backend parallel eager execution support (TBB, OpenMP, Parallel STL and in the future CUDA and OpenCL)
Example code for using Tensorflow 2.0 with both numerical and categorical data
This repository contains a notebook for object detection with the help of fine tuning of a (TF2 friendly) RetinaNet architecture on very few examples of a novel class after initializing from a pre-trained COCO checkpoint. Training runs in eager mode.
Foolbox Native brings native performance to Foolbox
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