436 Repositories
Python keras-notebooks Libraries
Learning from graph data using Keras
Steps to run = Download the cora dataset from this link : https://linqs.soe.ucsc.edu/data unzip the files in the folder input/cora cd code python eda
Keras Model Implementation Walkthrough
Keras Model Implementation Walkthrough
Pytorch and Keras Implementations of Hyperspectral Image Classification -- Traditional to Deep Models: A Survey for Future Prospects.
The repository contains the implementations for Hyperspectral Image Classification -- Traditional to Deep Models: A Survey for Future Prospects. Model
This is an implementation of Googles Yogi-Optimizer in Keras (tf.keras)
Yogi-Optimizer_Keras This is an implementation of Googles Yogi-Optimizer in Keras (tf.keras) The NeurIPS-Paper can be found here: http://papers.nips.c
A Keras implementation of YOLOv4 (Tensorflow backend)
keras-yolo4 请使用更完善的版本: https://github.com/miemie2013/Keras-YOLOv4 Please visit here for more complete model: https://github.com/miemie2013/Keras-YOLOv
📚 Papermill is a tool for parameterizing, executing, and analyzing Jupyter Notebooks.
papermill is a tool for parameterizing, executing, and analyzing Jupyter Notebooks. Papermill lets you: parameterize notebooks execute notebooks This
Tools for diffing and merging of Jupyter notebooks.
nbdime provides tools for diffing and merging of Jupyter Notebooks.
RISE allows you to instantly turn your Jupyter Notebooks into a slideshow
RISE RISE allows you to instantly turn your Jupyter Notebooks into a slideshow. No out-of-band conversion is needed, switch from jupyter notebook to a
An interactive grid for sorting, filtering, and editing DataFrames in Jupyter notebooks
qgrid Qgrid is a Jupyter notebook widget which uses SlickGrid to render pandas DataFrames within a Jupyter notebook. This allows you to explore your D
nbcommands bring the goodness of Unix commands to Jupyter notebooks.
nbcommands nbcommands bring the goodness of Unix commands to Jupyter notebooks. Installation You can simply use pip to install nbcommands: $ pip insta
Si Adek Keras is software VR dangerous object detection.
Si Adek Python Keras Sistem Informasi Deteksi Benda Berbahaya Keras Python. Version 1.0 Developed by Ananda Rauf Maududi. Developed date: 24 November
A TensorFlow 2.x implementation of Masked Autoencoders Are Scalable Vision Learners
Masked Autoencoders Are Scalable Vision Learners A TensorFlow implementation of Masked Autoencoders Are Scalable Vision Learners [1]. Our implementati
The fastai book, published as Jupyter Notebooks
English / Spanish / Korean / Chinese / Bengali / Indonesian The fastai book These notebooks cover an introduction to deep learning, fastai, and PyTorc
Unofficial keras(tensorflow) implementation of MAE model from Masked Autoencoders Are Scalable Vision Learners
MAE-keras Unofficial keras(tensorflow) implementation of MAE model described in 'Masked Autoencoders Are Scalable Vision Learners'. This work has been
Tensorflow 2.x implementation of Vision-Transformer model
Vision Transformer Unofficial Tensorflow 2.x implementation of the Transformer based Image Classification model proposed by the paper AN IMAGE IS WORT
An optimization and data collection toolbox for convenient and fast prototyping of computationally expensive models.
An optimization and data collection toolbox for convenient and fast prototyping of computationally expensive models. Hyperactive: is very easy to lear
State of the art faster Natural Language Processing in Tensorflow 2.0 .
tf-transformers: faster and easier state-of-the-art NLP in TensorFlow 2.0 ****************************************************************************
Live training loss plot in Jupyter Notebook for Keras, PyTorch and others
livelossplot Don't train deep learning models blindfolded! Be impatient and look at each epoch of your training! (RECENT CHANGES, EXAMPLES IN COLAB, A
Voilà turns Jupyter notebooks into standalone web applications
Rendering of live Jupyter notebooks with interactive widgets. Introduction Voilà turns Jupyter notebooks into standalone web applications. Unlike the
A keras-based real-time model for medical image segmentation (CFPNet-M)
CFPNet-M: A Light-Weight Encoder-Decoder Based Network for Multimodal Biomedical Image Real-Time Segmentation This repository contains the implementat
Lacmus is a cross-platform application that helps to find people who are lost in the forest using computer vision and neural networks.
lacmus The program for searching through photos from the air of lost people in the forest using Retina Net neural nwtwork. The project is being develo
Image classification for projects and researches
This is a tool to help you quickly solve classification problems including: data analysis, training, report results and model explanation.
Cascaded Pyramid Network (CPN) based on Keras (Tensorflow backend)
ML2 Takehome Project Reimplementing the paper: Cascaded Pyramid Network for Multi-Person Pose Estimation Dataset The model uses the COCO dataset which
Utilities for preprocessing text for deep learning with Keras
Note: This utility is really old and is no longer maintained. You should use keras.layers.TextVectorization instead of this. Utilities for pre-process
Hyperparameter tuning for humans
KerasTuner KerasTuner is an easy-to-use, scalable hyperparameter optimization framework that solves the pain points of hyperparameter search. Easily c
How to use TensorLayer
How to use TensorLayer While research in Deep Learning continues to improve the world, we use a bunch of tricks to implement algorithms with TensorLay
AutoML library for deep learning
Official Website: autokeras.com AutoKeras: An AutoML system based on Keras. It is developed by DATA Lab at Texas A&M University. The goal of AutoKeras
Keras implementation of AdaBound
AdaBound for Keras Keras port of AdaBound Optimizer for PyTorch, from the paper Adaptive Gradient Methods with Dynamic Bound of Learning Rate. Usage A
A Python toolbox to create adversarial examples that fool neural networks in PyTorch, TensorFlow, and JAX
Foolbox Native: Fast adversarial attacks to benchmark the robustness of machine learning models in PyTorch, TensorFlow, and JAX Foolbox is a Python li
Neural network graphs and training metrics for PyTorch, Tensorflow, and Keras.
HiddenLayer A lightweight library for neural network graphs and training metrics for PyTorch, Tensorflow, and Keras. HiddenLayer is simple, easy to ex
Source code and notebooks to reproduce experiments and benchmarks on Bias Faces in the Wild (BFW).
Face Recognition: Too Bias, or Not Too Bias? Robinson, Joseph P., Gennady Livitz, Yann Henon, Can Qin, Yun Fu, and Samson Timoner. "Face recognition:
Keras Implementation of Neural Style Transfer from the paper "A Neural Algorithm of Artistic Style"
Neural Style Transfer & Neural Doodles Implementation of Neural Style Transfer from the paper A Neural Algorithm of Artistic Style in Keras 2.0+ INetw
Machine learning notebooks in different subjects optimized to run in google collaboratory
Notebooks Name Description Category Link Training pix2pix This notebook shows a simple pipeline for training pix2pix on a simple dataset. Most of the
Lab Materials for MIT 6.S191: Introduction to Deep Learning
This repository contains all of the code and software labs for MIT 6.S191: Introduction to Deep Learning! All lecture slides and videos are available
Deep learning for NLP crash course at ABBYY.
Deep NLP Course at ABBYY Deep learning for NLP crash course at ABBYY. Suggested textbook: Neural Network Methods in Natural Language Processing by Yoa
Deep Learning tutorials in jupyter notebooks.
DeepSchool.io Sign up here for Udemy Course on Machine Learning (Use code DEEPSCHOOL-MARCH to get 85% off course). Goals Make Deep Learning easier (mi
Tutorials, assignments, and competitions for MIT Deep Learning related courses.
MIT Deep Learning This repository is a collection of tutorials for MIT Deep Learning courses. More added as courses progress. Tutorial: Deep Learning
Python Data Science Handbook: full text in Jupyter Notebooks
Python Data Science Handbook This repository contains the entire Python Data Science Handbook, in the form of (free!) Jupyter notebooks. How to Use th
DeepHyper: Scalable Asynchronous Neural Architecture and Hyperparameter Search for Deep Neural Networks
What is DeepHyper? DeepHyper is a software package that uses learning, optimization, and parallel computing to automate the design and development of
Introducing neural networks to predict stock prices
IntroNeuralNetworks in Python: A Template Project IntroNeuralNetworks is a project that introduces neural networks and illustrates an example of how o
This is a Machine Learning model which predicts the presence of Diabetes in Patients
Diabetes Disease Prediction This is a machine Learning mode which tries to determine if a person has a diabetes or not. Data The dataset is in comma s
Effect of Deep Transfer and Multi task Learning on Sperm Abnormality Detection
Effect of Deep Transfer and Multi task Learning on Sperm Abnormality Detection Introduction This repository includes codes and models of "Effect of De
A deep learning object detector framework written in Python for supporting Land Search and Rescue Missions.
AIR: Aerial Inspection RetinaNet for supporting Land Search and Rescue Missions AIR is a deep learning based object detection solution to automate the
Flower classification model that classifies flowers in 10 classes made using transfer learning (~85% accuracy).
flower-classification-inceptionV3 Flower classification model that classifies flowers in 10 classes. Training and validation are done using a pre-anot
A DCGAN to generate anime faces using custom mined dataset
Anime-Face-GAN-Keras A DCGAN to generate anime faces using custom dataset in Keras. Dataset The dataset is created by crawling anime database websites
GAN example for Keras. Cuz MNIST is too small and there should be something more realistic.
Keras-GAN-Animeface-Character GAN example for Keras. Cuz MNIST is too small and there should an example on something more realistic. Some results Trai
EfficientDet (Scalable and Efficient Object Detection) implementation in Keras and Tensorflow
EfficientDet This is an implementation of EfficientDet for object detection on Keras and Tensorflow. The project is based on the official implementati
🔎 Super-scale your images and run experiments with Residual Dense and Adversarial Networks.
Image Super-Resolution (ISR) The goal of this project is to upscale and improve the quality of low resolution images. This project contains Keras impl
An implementation of a sequence to sequence neural network using an encoder-decoder
Keras implementation of a sequence to sequence model for time series prediction using an encoder-decoder architecture. I created this post to share a
A framework for using LSTMs to detect anomalies in multivariate time series data. Includes spacecraft anomaly data and experiments from the Mars Science Laboratory and SMAP missions.
Telemanom (v2.0) v2.0 updates: Vectorized operations via numpy Object-oriented restructure, improved organization Merge branches into single branch fo
Provide an input CSV and a target field to predict, generate a model + code to run it.
automl-gs Give an input CSV file and a target field you want to predict to automl-gs, and get a trained high-performing machine learning or deep learn
A clean implementation based on AlphaZero for any game in any framework + tutorial + Othello/Gobang/TicTacToe/Connect4 and more
Alpha Zero General (any game, any framework!) A simplified, highly flexible, commented and (hopefully) easy to understand implementation of self-play
Open source hardware and software platform to build a small scale self driving car.
Donkeycar is minimalist and modular self driving library for Python. It is developed for hobbyists and students with a focus on allowing fast experimentation and easy community contributions.
Data science Python notebooks: Deep learning (TensorFlow, Theano, Caffe, Keras), scikit-learn, Kaggle, big data (Spark, Hadoop MapReduce, HDFS), matplotlib, pandas, NumPy, SciPy, Python essentials, AWS, and various command lines.
Data science Python notebooks: Deep learning (TensorFlow, Theano, Caffe, Keras), scikit-learn, Kaggle, big data (Spark, Hadoop MapReduce, HDFS), matplotlib, pandas, NumPy, SciPy, Python essentials, AWS, and various command lines.
Official Keras Implementation for UNet++ in IEEE Transactions on Medical Imaging and DLMIA 2018
UNet++: A Nested U-Net Architecture for Medical Image Segmentation UNet++ is a new general purpose image segmentation architecture for more accurate i
TensorFlow implementation of original paper : https://github.com/hszhao/PSPNet
Keras implementation of PSPNet(caffe) Implemented Architecture of Pyramid Scene Parsing Network in Keras. For the best compability please use Python3.
Keras implementation of Real-Time Semantic Segmentation on High-Resolution Images
Keras-ICNet [paper] Keras implementation of Real-Time Semantic Segmentation on High-Resolution Images. Training in progress! Requisites Python 3.6.3 K
DilatedNet in Keras for image segmentation
Keras implementation of DilatedNet for semantic segmentation A native Keras implementation of semantic segmentation according to Multi-Scale Context A
Keras Implementation of The One Hundred Layers Tiramisu: Fully Convolutional DenseNets for Semantic Segmentation by (Simon Jégou, Michal Drozdzal, David Vazquez, Adriana Romero, Yoshua Bengio)
The One Hundred Layers Tiramisu: Fully Convolutional DenseNets for Semantic Segmentation: Work In Progress, Results can't be replicated yet with the m
A keras implementation of ENet (abandoned for the foreseeable future)
ENet-keras This is an implementation of ENet: A Deep Neural Network Architecture for Real-Time Semantic Segmentation, ported from ENet-training (lua-t
A playable implementation of Fully Convolutional Networks with Keras.
keras-fcn A re-implementation of Fully Convolutional Networks with Keras Installation Dependencies keras tensorflow Install with pip $ pip install git
My implementation of Fully Convolutional Neural Networks in Keras
Keras-FCN This repository contains my implementation of Fully Convolutional Networks in Keras (Tensorflow backend). Currently, semantic segmentation c
Keras-tensorflow implementation of Fully Convolutional Networks for Semantic Segmentation(Unfinished)
Keras-FCN Fully convolutional networks and semantic segmentation with Keras. Models Models are found in models.py, and include ResNet and DenseNet bas
Keras implementation of Deeplab v3+ with pretrained weights
Keras implementation of Deeplabv3+ This repo is not longer maintained. I won't respond to issues but will merge PR DeepLab is a state-of-art deep lear
SegNet including indices pooling for Semantic Segmentation with tensorflow and keras
SegNet SegNet is a model of semantic segmentation based on Fully Comvolutional Network. This repository contains the implementation of learning and te
SegNet-Basic with Keras
SegNet-Basic: What is Segnet? Deep Convolutional Encoder-Decoder Architecture for Semantic Pixel-wise Image Segmentation Segnet = (Encoder + Decoder)
SegNet model implemented using keras framework
keras-segnet Implementation of SegNet-like architecture using keras. Current version doesn't support index transferring proposed in SegNet article, so
Segmentation models with pretrained backbones. Keras and TensorFlow Keras.
Python library with Neural Networks for Image Segmentation based on Keras and TensorFlow. The main features of this library are: High level API (just
Implementation of Segnet, FCN, UNet , PSPNet and other models in Keras.
Image Segmentation Keras : Implementation of Segnet, FCN, UNet, PSPNet and other models in Keras. Implementation of various Deep Image Segmentation mo
U-Net: Convolutional Networks for Biomedical Image Segmentation
Deep Learning Tutorial for Kaggle Ultrasound Nerve Segmentation competition, using Keras This tutorial shows how to use Keras library to build deep ne
Modification of convolutional neural net "UNET" for image segmentation in Keras framework
ZF_UNET_224 Pretrained Model Modification of convolutional neural net "UNET" for image segmentation in Keras framework Requirements Python 3.*, Keras
Kaggle Ultrasound Nerve Segmentation competition [Keras]
Ultrasound nerve segmentation using Keras (1.0.7) Kaggle Ultrasound Nerve Segmentation competition [Keras] #Install (Ubuntu {14,16}, GPU) cuDNN requir
Deep Learning Tutorial for Kaggle Ultrasound Nerve Segmentation competition, using Keras
Deep Learning Tutorial for Kaggle Ultrasound Nerve Segmentation competition, using Keras This tutorial shows how to use Keras library to build deep ne
unet for image segmentation
Implementation of deep learning framework -- Unet, using Keras The architecture was inspired by U-Net: Convolutional Networks for Biomedical Image Seg
The main aim of this project is to avoid the accidents in shredding ( Waste Recycling Industry )
shredder-Machine-Hand-Safety The main aim of this project is to avoid the accidents in shredding ( Waste Recycling Industry ) . The Basic function of
Models Supported: AlbUNet [18, 34, 50, 101, 152] (1D and 2D versions for Single and Multiclass Segmentation, Feature Extraction with supports for Deep Supervision and Guided Attention)
AlbUNet-1D-2D-Tensorflow-Keras This repository contains 1D and 2D Signal Segmentation Model Builder for AlbUNet and several of its variants developed
Interactive convnet features visualization for Keras
Quiver Interactive convnet features visualization for Keras The quiver workflow Video Demo Build your model in keras model = Model(...) Launch the vis
We have built a Voice based Personal Assistant for people to access files hands free in their device using natural language processing.
Voice Based Personal Assistant We have built a Voice based Personal Assistant for people to access files hands free in their device using natural lang
Notebooks em Python para Métodos Eletromagnéticos
GeoSci Labs This is a repository of code used to power the notebooks and interactive examples for https://em.geosci.xyz and https://gpg.geosci.xyz. Th
nbsafety adds a layer of protection to computational notebooks by solving the stale dependency problem when executing cells out-of-order
nbsafety adds a layer of protection to computational notebooks by solving the stale dependency problem when executing cells out-of-order
TensorFlow 2 implementation of the Yahoo Open-NSFW model
TensorFlow 2 implementation of the Yahoo Open-NSFW model
Digital Earth Australia notebooks and tools repository
Repository for Digital Earth Australia Jupyter Notebooks: tools and workflows for geospatial analysis with Open Data Cube and xarray
Beyond a Gaussian Denoiser: Residual Learning of Deep CNN for Image Denoising
Beyond a Gaussian Denoiser: Residual Learning of Deep CNN for Image Denoising
This is a Keras implementation of a CNN for estimating age, gender and mask from a camera.
face-detector-age-gender This is a Keras implementation of a CNN for estimating age, gender and mask from a camera. Before run face detector app, expr
Regression Metrics Calculation Made easy for tensorflow2 and scikit-learn
Regression Metrics Installation To install the package from the PyPi repository you can execute the following command: pip install regressionmetrics I
Tensorflow implementation and notebooks for Implicit Maximum Likelihood Estimation
tf-imle Tensorflow 2 and PyTorch implementation and Jupyter notebooks for Implicit Maximum Likelihood Estimation (I-MLE) proposed in the NeurIPS 2021
Covid-19 Test AI (Deep Learning - NNs) Software. Accuracy is the %96.5, loss is the 0.09 :)
Covid-19 Test AI (Deep Learning - NNs) Software I developed a segmentation algorithm to understand whether Covid-19 Test Photos are positive or negati
Hierarchical probabilistic 3D U-Net, with attention mechanisms (—𝘈𝘵𝘵𝘦𝘯𝘵𝘪𝘰𝘯 𝘜-𝘕𝘦𝘵, 𝘚𝘌𝘙𝘦𝘴𝘕𝘦𝘵) and a nested decoder structure with deep supervision (—𝘜𝘕𝘦𝘵++).
Hierarchical probabilistic 3D U-Net, with attention mechanisms (—𝘈𝘵𝘵𝘦𝘯𝘵𝘪𝘰𝘯 𝘜-𝘕𝘦𝘵, 𝘚𝘌𝘙𝘦𝘴𝘕𝘦𝘵) and a nested decoder structure with deep supervision (—𝘜𝘕𝘦𝘵++). Built in TensorFlow 2.5. Configured for voxel-level clinically significant prostate cancer detection in multi-channel 3D bpMRI scans.
Implementation of ConvMixer-Patches Are All You Need? in TensorFlow and Keras
Patches Are All You Need? - ConvMixer ConvMixer, an extremely simple model that is similar in spirit to the ViT and the even-more-basic MLP-Mixer in t
Convolutional neural network web app trained to track our infant’s sleep schedule using our Google Nest camera.
Machine Learning Sleep Schedule Tracker What is it? Convolutional neural network web app trained to track our infant’s sleep schedule using our Google
🦩 A Python tool to create comment-free Jupyter notebooks.
Pelikan Pelikan lets you convert notebooks to comment-free notebooks. In other words, It removes Python block and inline comments from source cells in
Vision Deep-Learning using Tensorflow, Keras.
Welcome! I am a computer vision deep learning developer working in Korea. This is my blog, and you can see everything I've studied here. https://www.n
Supplemental Code for "ImpressionNet :A Multi view Approach to Predict Socio Facial Impressions"
Supplemental Code for "ImpressionNet :A Multi view Approach to Predict Socio Facial Impressions" Environment requirement This code is based on Python
Train a state-of-the-art yolov3 object detector from scratch!
TrainYourOwnYOLO: Building a Custom Object Detector from Scratch This repo let's you train a custom image detector using the state-of-the-art YOLOv3 c
Code repository of the paper Neural circuit policies enabling auditable autonomy published in Nature Machine Intelligence
Code repository of the paper Neural circuit policies enabling auditable autonomy published in Nature Machine Intelligence
Finetuner allows one to tune the weights of any deep neural network for better embeddings on search tasks
Finetuner allows one to tune the weights of any deep neural network for better embeddings on search tasks
Flower - A Friendly Federated Learning Framework
Flower - A Friendly Federated Learning Framework Flower (flwr) is a framework for building federated learning systems. The design of Flower is based o
Code repository of the paper Neural circuit policies enabling auditable autonomy published in Nature Machine Intelligence
Neural Circuit Policies Enabling Auditable Autonomy Online access via SharedIt Neural Circuit Policies (NCPs) are designed sparse recurrent neural net
The "breathing k-means" algorithm with datasets and example notebooks
The Breathing K-Means Algorithm (with examples) The Breathing K-Means is an approximation algorithm for the k-means problem that (on average) is bette
Identify the emotion of multiple speakers in an Audio Segment
MevonAI - Speech Emotion Recognition Identify the emotion of multiple speakers in a Audio Segment Report Bug · Request Feature Try the Demo Here Table