1448 Repositories
Python tensorflow-training Libraries
Multi-label classification of retinal disorders
Multi-label classification of retinal disorders This is a deep learning course project. The goal is to develop a solution, using computer vision techn
TensorFlow implementation for Bayesian Modeling and Uncertainty Quantification for Learning to Optimize: What, Why, and How
Bayesian Modeling and Uncertainty Quantification for Learning to Optimize: What, Why, and How TensorFlow implementation for Bayesian Modeling and Unce
JASS: Japanese-specific Sequence to Sequence Pre-training for Neural Machine Translation
JASS: Japanese-specific Sequence to Sequence Pre-training for Neural Machine Translation This the repository for this paper. Find extensions of this w
WPPNets: Unsupervised CNN Training with Wasserstein Patch Priors for Image Superresolution
WPPNets: Unsupervised CNN Training with Wasserstein Patch Priors for Image Superresolution This code belongs to the paper [1] available at https://arx
For encoding a text longer than 512 tokens, for example 800. Set max_pos to 800 during both preprocessing and training.
LongScientificFormer For encoding a text longer than 512 tokens, for example 800. Set max_pos to 800 during both preprocessing and training. Some code
GND-Nets (Graph Neural Diffusion Networks) in TensorFlow.
GNDC For submission to IEEE TKDE. Overview Here we provide the implementation of GND-Nets (Graph Neural Diffusion Networks) in TensorFlow. The reposit
Framework for training options with different attention mechanism and using them to solve downstream tasks.
Using Attention in HRL Framework for training options with different attention mechanism and using them to solve downstream tasks. Requirements GPU re
Identifying a Training-Set Attack’s Target Using Renormalized Influence Estimation
Identifying a Training-Set Attack’s Target Using Renormalized Influence Estimation By: Zayd Hammoudeh and Daniel Lowd Paper: Arxiv Preprint Coming soo
Post-training Quantization for Neural Networks with Provable Guarantees
Post-training Quantization for Neural Networks with Provable Guarantees Authors: Jinjie Zhang ([email protected]), Yixuan Zhou ([email protected]) and Ray
Semantic code search implementation using Tensorflow framework and the source code data from the CodeSearchNet project
Semantic Code Search Semantic code search implementation using Tensorflow framework and the source code data from the CodeSearchNet project. The model
Style transfer between images was performed using the VGG19 model
Style transfer between images was performed using the VGG19 model. The necessary codes, libraries and all other information of this project are available below
Audio Source Separation is the process of separating a mixture into isolated sounds from individual sources
Audio Source Separation is the process of separating a mixture into isolated sounds from individual sources (e.g. just the lead vocals).
ECAENet (TensorFlow and Keras)
ECAENet: EfficientNet with Efficient Channel Attention for Plant Species Recognition (SCI:Q3) (Journal of Intelligent & Fuzzy Systems)
SAS: Self-Augmentation Strategy for Language Model Pre-training
SAS: Self-Augmentation Strategy for Language Model Pre-training This repository
Revisiting Weakly Supervised Pre-Training of Visual Perception Models
SWAG: Supervised Weakly from hashtAGs This repository contains SWAG models from the paper Revisiting Weakly Supervised Pre-Training of Visual Percepti
Cycle Self-Training for Domain Adaptation (NeurIPS 2021)
CST Code release for "Cycle Self-Training for Domain Adaptation" (NeurIPS 2021) Prerequisites torch=1.7.0 torchvision qpsolvers numpy prettytable tqd
Labelbox is the fastest way to annotate data to build and ship artificial intelligence applications
Labelbox Labelbox is the fastest way to annotate data to build and ship artificial intelligence applications. Use this github repository to help you s
CVAT is free, online, interactive video and image annotation tool for computer vision
Computer Vision Annotation Tool (CVAT) CVAT is free, online, interactive video and image annotation tool for computer vision. It is being used by our
CLIP (Contrastive Language-Image Pre-Training) is a neural network trained on a variety of (image, text) pairs
CLIP [Blog] [Paper] [Model Card] [Colab] CLIP (Contrastive Language-Image Pre-Training) is a neural network trained on a variety of (image, text) pair
The repository includes the code for training cell counting applications. (Keras + Tensorflow)
cell_counting_v2 The repository includes the code for training cell counting applications. (Keras + Tensorflow) Dataset can be downloaded here : http:
Pre-trained models for a Cascaded-FCN in caffe and tensorflow that segments
Cascaded-FCN This repository contains the pre-trained models for a Cascaded-FCN in caffe and tensorflow that segments the liver and its lesions out of
Here we present the implementation in TensorFlow of our work about liver lesion segmentation accepted in the Machine Learning 4 Health Workshop
Detection-aided liver lesion segmentation Here we present the implementation in TensorFlow of our work about liver lesion segmentation accepted in the
Source code of all the projects of Udacity Self-Driving Car Engineer Nanodegree.
self-driving-car In this repository I will share the source code of all the projects of Udacity Self-Driving Car Engineer Nanodegree. Hope this might
A collection of semantic image segmentation models implemented in TensorFlow
A collection of semantic image segmentation models implemented in TensorFlow. Contains data-loaders for the generic and medical benchmark datasets.
Segmentation Training Pipeline
Segmentation Training Pipeline This package is a part of Musket ML framework. Reasons to use Segmentation Pipeline Segmentation Pipeline was developed
PyTorchMemTracer - Depict GPU memory footprint during DNN training of PyTorch
A Memory Tracer For PyTorch OOM is a nightmare for PyTorch users. However, most
A deep neural networks for images using CNN algorithm.
Example-CNN-Project This is a simple project showing how to implement deep neural networks using CNN algorithm. The dataset is taken from this link: h
First steps with Python in Life Sciences
First steps with Python in Life Sciences This course material is part of the "First Steps with Python in Life Science" three-day course of SIB-trainin
This project generates news headlines using a Long Short-Term Memory (LSTM) neural network.
News Headlines Generator bunnysaini/Generate-Headlines Goal This project aims to generate news headlines using a Long Short-Term Memory (LSTM) neural
Use Tensorflow2.7.0 Build OpenAI'GPT-2
TF2_GPT-2 Use Tensorflow2.7.0 Build OpenAI'GPT-2 使用最新tensorflow2.7.0构建openai官方的GPT-2 NLP模型 优点 使用无监督技术 拥有大量词汇量 可实现续写(堪比“xx梦续写”) 实现对话后续将应用于FloatTech的Bot
Collapse by Conditioning: Training Class-conditional GANs with Limited Data
Collapse by Conditioning: Training Class-conditional GANs with Limited Data Moha
ESGD-M - A stochastic non-convex second order optimizer, suitable for training deep learning models, for PyTorch
ESGD-M - A stochastic non-convex second order optimizer, suitable for training deep learning models, for PyTorch
HistoSeg : Quick attention with multi-loss function for multi-structure segmentation in digital histology images
HistoSeg : Quick attention with multi-loss function for multi-structure segmentation in digital histology images Histological Image Segmentation This
TensorDebugger (TDB) is a visual debugger for deep learning. It extends TensorFlow with breakpoints + real-time visualization of the data flowing through the computational graph
TensorDebugger (TDB) is a visual debugger for deep learning. It extends TensorFlow (Google's Deep Learning framework) with breakpoints + real-time visualization of the data flowing through the computational graph.
Repo for investigation of timeouts that happens with prolonged training on clients
Flower-timeout Repo for investigation of timeouts that happens with prolonged training on clients. This repository is meant purely for demonstration o
GitHub Actions Docker training
GitHub-Actions-Docker-training Training exercise repository for GitHub Actions using a docker base. This repository should be cloned and used for trai
TLXZoo - Pre-trained models based on TensorLayerX
Pre-trained models based on TensorLayerX. TensorLayerX is a multi-backend AI fra
This Deep Learning Model Predicts that from which disease you are suffering.
Deep-Learning-Project This Deep Learning Model Predicts that from which disease you are suffering. This Project Covers the Topics of Deep Learning Int
GNES enables large-scale index and semantic search for text-to-text, image-to-image, video-to-video and any-to-any content form
GNES is Generic Neural Elastic Search, a cloud-native semantic search system based on deep neural network.
Circuit Training: An open-source framework for generating chip floor plans with distributed deep reinforcement learning
Circuit Training: An open-source framework for generating chip floor plans with distributed deep reinforcement learning. Circuit Training is an open-s
X-VLM: Multi-Grained Vision Language Pre-Training
X-VLM: learning multi-grained vision language alignments Multi-Grained Vision Language Pre-Training: Aligning Texts with Visual Concepts. Yan Zeng, Xi
ColossalAI-Examples - Examples of training models with hybrid parallelism using ColossalAI
ColossalAI-Examples This repository contains examples of training models with Co
A Next Generation ConvNet by FaceBookResearch Implementation in PyTorch(Original) and TensorFlow.
ConvNeXt A Next Generation ConvNet by FaceBookResearch Implementation in PyTorch(Original) and TensorFlow. A FacebookResearch Implementation on A Conv
A novel Engagement Detection with Multi-Task Training (ED-MTT) system
A novel Engagement Detection with Multi-Task Training (ED-MTT) system which minimizes MSE and triplet loss together to determine the engagement level of students in an e-learning environment.
TiP-Adapter: Training-free CLIP-Adapter for Better Vision-Language Modeling
TiP-Adapter: Training-free CLIP-Adapter for Better Vision-Language Modeling This is the official code release for the paper 'TiP-Adapter: Training-fre
A PyTorch implementation of VIOLET
VIOLET: End-to-End Video-Language Transformers with Masked Visual-token Modeling A PyTorch implementation of VIOLET Overview VIOLET is an implementati
This is the repository for The Machine Learning Workshops, published by AI DOJO
This is the repository for The Machine Learning Workshops, published by AI DOJO. It contains all the workshop's code with supporting project files necessary to work through the code.
A CNN model to detect hand gestures.
Software Used python - programming language used, tested on v3.8 miniconda - for managing virtual environment Libraries Used opencv - pip install open
Brain Tumor Detection with Tensorflow Neural Networks.
Brain-Tumor-Detection A convolutional neural network model built with Tensorflow & Keras to detect brain tumor and its different variants. Data of the
TFOD-MASKRCNN - Tensorflow MaskRCNN With Python
Tensorflow- MaskRCNN Steps git clone https://github.com/amalaj7/TFOD-MASKRCNN.gi
A complete, self-contained example for training ImageNet at state-of-the-art speed with FFCV
ffcv ImageNet Training A minimal, single-file PyTorch ImageNet training script designed for hackability. Run train_imagenet.py to get... ...high accur
"Moshpit SGD: Communication-Efficient Decentralized Training on Heterogeneous Unreliable Devices", official implementation
Moshpit SGD: Communication-Efficient Decentralized Training on Heterogeneous Unreliable Devices This repository contains the official PyTorch implemen
OneShot Learning-based hotword detection.
EfficientWord-Net Hotword detection based on one-shot learning Home assistants require special phrases called hotwords to get activated (eg:"ok google
Face Mask Detector by live camera using tensorflow-keras, openCV and Python
Face Mask Detector 😷 by Live Camera Detecting masked or unmasked faces by live camera with percentange of mask occupation About Project: This an Arti
Implement of "Training deep neural networks via direct loss minimization" in PyTorch for 0-1 loss
This is the implementation of "Training deep neural networks via direct loss minimization" published at ICML 2016 in PyTorch. The implementation targe
Pianote - An application that helps musicians practice piano ear training
Pianote Pianote is an application that helps musicians practice piano ear traini
🔎 Monitor deep learning model training and hardware usage from your mobile phone 📱
Monitor deep learning model training and hardware usage from mobile. 🔥 Features Monitor running experiments from mobile phone (or laptop) Monitor har
Code for Reciprocal Adversarial Learning for Brain Tumor Segmentation: A Solution to BraTS Challenge 2021 Segmentation Task
BRATS 2021 Solution For Segmentation Task This repo contains the supported pytorch code and configuration files to reproduce 3D medical image segmenta
This repo generates the training data and the model for Morpheus-Deblend
Morpheus-Deblend This repo generates the training data and the model for Morpheus-Deblend. This is the active development repo for the project and as
Collection of machine learning related notebooks to share.
ML_Notebooks Collection of machine learning related notebooks to share. Notebooks GAN_distributed_training.ipynb In this Notebook, TensorFlow's tutori
Simple helper library to convert a collection of numpy data to tfrecord, and build a tensorflow dataset from the tfrecord.
numpy2tfrecord Simple helper library to convert a collection of numpy data to tfrecord, and build a tensorflow dataset from the tfrecord. Installation
Simple Tensorflow implementation of Toward Spatially Unbiased Generative Models (ICCV 2021)
Spatial unbiased GANs — Simple TensorFlow Implementation [Paper] : Toward Spatially Unbiased Generative Models (ICCV 2021) Abstract Recent image gener
The final project of "Applying AI to 3D Medical Imaging Data" from "AI for Healthcare" nanodegree - Udacity.
Quantifying Hippocampus Volume for Alzheimer's Progression Background Alzheimer's disease (AD) is a progressive neurodegenerative disorder that result
IA for recognising Traffic Signs using Keras [Tensorflow]
Traffic Signs Recognition ⚠️ 🚦 Fundamentals of Intelligent Systems Introduction 📄 Development of a neural network capable of recognizing nine differ
The code for our paper Semi-Supervised Learning with Multi-Head Co-Training
Semi-Supervised Learning with Multi-Head Co-Training (PyTorch) Abstract Co-training, extended from self-training, is one of the frameworks for semi-su
Weakly Supervised Segmentation with Tensorflow. Implements instance segmentation as described in Simple Does It: Weakly Supervised Instance and Semantic Segmentation, by Khoreva et al. (CVPR 2017).
Weakly Supervised Segmentation with TensorFlow This repo contains a TensorFlow implementation of weakly supervised instance segmentation as described
Explores the python bytecode, provides some tools to access it for fun and profit.
Pyasmtools - looking at the python bytecode for fun and profit. The pyasmtools library is made up of two parts A python bytecode disassembler . See Py
Convnext-tf - Unofficial tensorflow keras implementation of ConvNeXt
ConvNeXt Tensorflow This is unofficial tensorflow keras implementation of ConvNe
A Python module for the generation and training of an entry-level feedforward neural network.
ff-neural-network A Python module for the generation and training of an entry-level feedforward neural network. This repository serves as a repurposin
Training a Resilient Q-Network against Observational Interference, Causal Inference Q-Networks
Obs-Causal-Q-Network AAAI 2022 - Training a Resilient Q-Network against Observational Interference Preprint | Slides | Colab Demo | Environment Setup
World Models with TensorFlow 2
World Models This repo reproduces the original implementation of World Models. This implementation uses TensorFlow 2.2. Docker The easiest way to hand
Intel® Neural Compressor is an open-source Python library running on Intel CPUs and GPUs
Intel® Neural Compressor targeting to provide unified APIs for network compression technologies, such as low precision quantization, sparsity, pruning, knowledge distillation, across different deep learning frameworks to pursue optimal inference performance.
Unofficial Tensorflow Implementation of ConvNeXt from A ConvNet for the 2020s
Tensorflow Implementation of "A ConvNet for the 2020s" This is the unofficial Tensorflow Implementation of ConvNeXt from "A ConvNet for the 2020s" pap
Mapping a variable-length sentence to a fixed-length vector using BERT model
Are you looking for X-as-service? Try the Cloud-Native Neural Search Framework for Any Kind of Data bert-as-service Using BERT model as a sentence enc
Tensorflow2.0 🍎🍊 is delicious, just eat it! 😋😋
How to eat TensorFlow2 in 30 days ? 🔥 🔥 Click here for Chinese Version(中文版) 《10天吃掉那只pyspark》 🚀 github项目地址: https://github.com/lyhue1991/eat_pyspark
YoloV3 Implemented in Tensorflow 2.0
YoloV3 Implemented in TensorFlow 2.0 This repo provides a clean implementation of YoloV3 in TensorFlow 2.0 using all the best practices. Key Features
A set of Deep Reinforcement Learning Agents implemented in Tensorflow.
Deep Reinforcement Learning Agents This repository contains a collection of reinforcement learning algorithms written in Tensorflow. The ipython noteb
subpixel: A subpixel convnet for super resolution with Tensorflow
subpixel: A subpixel convolutional neural network implementation with Tensorflow Left: input images / Right: output images with 4x super-resolution af
Practical tutorials and labs for TensorFlow used by Nvidia, FFN, CNN, RNN, Kaggle, AE
TensorFlow Tutorial - used by Nvidia Learn TensorFlow from scratch by examples and visualizations with interactive jupyter notebooks. Learn to compete
Scenarios, tutorials and demos for Autonomous Driving
The Autonomous Driving Cookbook (Preview) NOTE: This project is developed and being maintained by Project Road Runner at Microsoft Garage. This is cur
Practical Machine Learning with Python
Master the essential skills needed to recognize and solve complex real-world problems with Machine Learning and Deep Learning by leveraging the highly popular Python Machine Learning Eco-system.
Chess reinforcement learning by AlphaGo Zero methods.
About Chess reinforcement learning by AlphaGo Zero methods. This project is based on these main resources: DeepMind's Oct 19th publication: Mastering
The official TensorFlow implementation of the paper Action Transformer: A Self-Attention Model for Short-Time Pose-Based Human Action Recognition
Action Transformer A Self-Attention Model for Short-Time Human Action Recognition This repository contains the official TensorFlow implementation of t
Soft actor-critic is a deep reinforcement learning framework for training maximum entropy policies in continuous domains.
This repository is no longer maintained. Please use our new Softlearning package instead. Soft Actor-Critic Soft actor-critic is a deep reinforcement
Supervised 3D Pre-training on Large-scale 2D Natural Image Datasets for 3D Medical Image Analysis
Introduction This is an implementation of our paper Supervised 3D Pre-training on Large-scale 2D Natural Image Datasets for 3D Medical Image Analysis.
for a paper about leveraging discourse markers for training new models
TSLM-DISCOURSE-MARKERS Scope This repository contains: (1) Code to extract discourse markers from wikipedia (TSA). (1) Code to extract significant dis
Machine Learning Model deployment for Container (TensorFlow Serving)
try_tf_serving ├───dataset │ ├───testing │ │ ├───paper │ │ ├───rock │ │ └───scissors │ └───training │ ├───paper │ ├───rock
Deep learning with TensorFlow and earth observation data.
Deep Learning with TensorFlow and EO Data Complete file set for Jupyter Book Autor: Development Seed Date: 04 October 2021 ISBN: (to come) Notebook tu
Notebooks for my "Deep Learning with TensorFlow 2 and Keras" course
Deep Learning with TensorFlow 2 and Keras – Notebooks This project accompanies my Deep Learning with TensorFlow 2 and Keras trainings. It contains the
A Keras implementation of YOLOv3 (Tensorflow backend)
keras-yolo3 Introduction A Keras implementation of YOLOv3 (Tensorflow backend) inspired by allanzelener/YAD2K. Quick Start Download YOLOv3 weights fro
Deep Learning and Reinforcement Learning Library for Scientists and Engineers 🔥
TensorLayer is a novel TensorFlow-based deep learning and reinforcement learning library designed for researchers and engineers. It provides an extens
Translate darknet to tensorflow. Load trained weights, retrain/fine-tune using tensorflow, export constant graph def to mobile devices
Intro Real-time object detection and classification. Paper: version 1, version 2. Read more about YOLO (in darknet) and download weight files here. In
MTCNN face detection implementation for TensorFlow, as a PIP package.
MTCNN Implementation of the MTCNN face detector for Keras in Python3.4+. It is written from scratch, using as a reference the implementation of MTCNN
This repo contains the implementation of YOLOv2 in Keras with Tensorflow backend.
Easy training on custom dataset. Various backends (MobileNet and SqueezeNet) supported. A YOLO demo to detect raccoon run entirely in brower is accessible at https://git.io/vF7vI (not on Windows).
Gathers machine learning and Tensorflow deep learning models for NLP problems, 1.13 Tensorflow 2.0
NLP-Models-Tensorflow, Gathers machine learning and tensorflow deep learning models for NLP problems, code simplify inside Jupyter Notebooks 100%. Tab
🙄 Difficult algorithm, Simple code.
🎉TensorFlow2.0-Examples🎉! "Talk is cheap, show me the code." ----- Linus Torvalds Created by YunYang1994 This tutorial was designed for easily divin
Official Implementation for Fast Training of Neural Lumigraph Representations using Meta Learning.
Fast Training of Neural Lumigraph Representations using Meta Learning Project Page | Paper | Data Alexander W. Bergman, Petr Kellnhofer, Gordon Wetzst
A Neural Network based chess engine and GUI made with Python and Tensorflow/Keras.
Haxaw-Chess Haxaw: Haxaw is the Neural Network based chess engine made with Python and Tensorflow/Keras. Also uses the python-chess library. (WIP: Imp
Tensorflow implementation of paper: Learning to Diagnose with LSTM Recurrent Neural Networks.
Multilabel time series classification with LSTM Tensorflow implementation of model discussed in the following paper: Learning to Diagnose with LSTM Re
TensorFlow implementation of Elastic Weight Consolidation
Elastic weight consolidation Introduction A TensorFlow implementation of elastic weight consolidation as presented in Overcoming catastrophic forgetti