4872 Repositories
Python DNA-sequence-classification-by-Deep-Neural-Network Libraries
Deeprl - Standard DQN and dueling network for simple games
DeepRL This code implements the standard deep Q-learning and dueling network with experience replay (memory buffer) for playing simple games. DQN algo
Deep Residual Learning for Image Recognition
Deep Residual Learning for Image Recognition This is a Torch implementation of "Deep Residual Learning for Image Recognition",Kaiming He, Xiangyu Zhan
Deep Inside Convolutional Networks - This is a caffe implementation to visualize the learnt model
Deep Inside Convolutional Networks This is a caffe implementation to visualize the learnt model. Part of a class project at Georgia Tech Problem State
OverFeat is a Convolutional Network-based image classifier and feature extractor.
OverFeat OverFeat is a Convolutional Network-based image classifier and feature extractor. OverFeat was trained on the ImageNet dataset and participat
C3d-pytorch - Pytorch porting of C3D network, with Sports1M weights
C3D for pytorch This is a pytorch porting of the network presented in the paper Learning Spatiotemporal Features with 3D Convolutional Networks How to
Code release for Convolutional Two-Stream Network Fusion for Video Action Recognition
Convolutional Two-Stream Network Fusion for Video Action Recognition
Deep-Learning-Image-Captioning - Implementing convolutional and recurrent neural networks in Keras to generate sentence descriptions of images
Deep Learning - Image Captioning with Convolutional and Recurrent Neural Nets ========================================================================
Image captioning - Tensorflow implementation of Show, Attend and Tell: Neural Image Caption Generation with Visual Attention
Introduction This neural system for image captioning is roughly based on the paper "Show, Attend and Tell: Neural Image Caption Generation with Visual
Seq2seq - Sequence to Sequence Learning with Keras
Seq2seq Sequence to Sequence Learning with Keras Hi! You have just found Seq2Seq. Seq2Seq is a sequence to sequence learning add-on for the python dee
Nmt - TensorFlow Neural Machine Translation Tutorial
Neural Machine Translation (seq2seq) Tutorial Authors: Thang Luong, Eugene Brevdo, Rui Zhao (Google Research Blogpost, Github) This version of the tut
Computer-Vision-Paper-Reviews - Computer Vision Paper Reviews with Key Summary along Papers & Codes
Computer-Vision-Paper-Reviews Computer Vision Paper Reviews with Key Summary along Papers & Codes. Jonathan Choi 2021 50+ Papers across Computer Visio
NLP-Project - Used an API to scrape 2000 reddit posts, then used NLP analysis and created a classification model to mixed succcess
Project 3: Web APIs & NLP Problem Statement How do r/Libertarian and r/Neoliberal differ on Biden post-inaguration? The goal of the project is to see
[3DV 2021] Channel-Wise Attention-Based Network for Self-Supervised Monocular Depth Estimation
Channel-Wise Attention-Based Network for Self-Supervised Monocular Depth Estimation This is the official implementation for the method described in Ch
SimpleDepthEstimation - An unified codebase for NN-based monocular depth estimation methods
SimpleDepthEstimation Introduction This is an unified codebase for NN-based monocular depth estimation methods, the framework is based on detectron2 (
Code for our SIGCOMM'21 paper "Network Planning with Deep Reinforcement Learning".
0. Introduction This repository contains the source code for our SIGCOMM'21 paper "Network Planning with Deep Reinforcement Learning". Notes The netwo
LightningFSL: Pytorch-Lightning implementations of Few-Shot Learning models.
LightningFSL: Few-Shot Learning with Pytorch-Lightning In this repo, a number of pytorch-lightning implementations of FSL algorithms are provided, inc
Benchmark VAE - Library for Variational Autoencoder benchmarking
Documentation pythae This library implements some of the most common (Variational) Autoencoder models. In particular it provides the possibility to pe
A video scene detection algorithm is designed to detect a variety of different scenes within a video
Scene-Change-Detection - A video scene detection algorithm is designed to detect a variety of different scenes within a video. There is a very simple definition for a scene: It is a series of logically and chronologically related shots taken in a specific order to depict an over-arching concept or story.
LSTM based Sentiment Classification using Tensorflow - Amazon Reviews Rating
LSTM based Sentiment Classification using Tensorflow - Amazon Reviews Rating (Dataset) The dataset is from Amazon Review Data (2018)
MLR - Machine Learning Research
Machine Learning Research 1. Project Topic 1.1. Exsiting research Benmark: https://paperswithcode.com/sota ACL anthology for NLP papers: http://www.ac
Centauro - a command line tool with some network management functionality
Centauro Ferramenta de rede O Centauro é uma ferramenta de linha de comando com
Simple-Image-Classification - Simple Image Classification Code (PyTorch)
Simple-Image-Classification Simple Image Classification Code (PyTorch) Yechan Kim This repository contains: Python3 / Pytorch code for multi-class ima
Python wrapper class for OpenVINO Model Server. User can submit inference request to OVMS with just a few lines of code
Python wrapper class for OpenVINO Model Server. User can submit inference request to OVMS with just a few lines of code.
BasicNeuralNetwork - This project looks over the basic structure of a neural network and how machine learning training algorithms work
BasicNeuralNetwork - This project looks over the basic structure of a neural network and how machine learning training algorithms work. For this project, I used the sigmoid function as an activation function along with stochastic gradient descent to adjust the weights and biases.
Deep-Learning-Book-Chapter-Summaries - Attempting to make the Deep Learning Book easier to understand.
Deep-Learning-Book-Chapter-Summaries This repository provides a summary for each chapter of the Deep Learning book by Ian Goodfellow, Yoshua Bengio an
Awesome Artificial Intelligence, Machine Learning and Deep Learning as we learn it
Awesome Artificial Intelligence, Machine Learning and Deep Learning as we learn it. Study notes and a curated list of awesome resources of such topics.
Osmnx-examples - Usage examples, demos, and tutorials for OSMnx.
OSMnx Examples OSMnx is a Python package to work with street networks and other spatial data from OpenStreetMap: retrieve, model, analyze, and visuali
Snake - Code for "Deep Snake for Real-Time Instance Segmentation" CVPR 2020 oral
Good news! Snake algorithms exhibit state-of-the-art performances on COCO dataset: DANCE Deep Snake for Real-Time Instance Segmentation Deep Snake for
Awesome-AI-books - Some awesome AI related books and pdfs for learning and downloading
Awesome AI books Some awesome AI related books and pdfs for downloading and learning. Preface This repo only used for learning, do not use in business
Awesome Graph Classification - A collection of important graph embedding, classification and representation learning papers with implementations.
A collection of graph classification methods, covering embedding, deep learning, graph kernel and factorization papers
Augmented Traffic Control: A tool to simulate network conditions
Augmented Traffic Control Full documentation for the project is available at http://facebook.github.io/augmented-traffic-control/. Overview Augmented
Deep-learning-roadmap - All You Need to Know About Deep Learning - A kick-starter
Deep Learning - All You Need to Know Sponsorship To support maintaining and upgrading this project, please kindly consider Sponsoring the project deve
Tianshou - An elegant PyTorch deep reinforcement learning library.
Tianshou (天授) is a reinforcement learning platform based on pure PyTorch. Unlike existing reinforcement learning libraries, which are mainly based on
AutoGluon: AutoML for Text, Image, and Tabular Data
AutoML for Text, Image, and Tabular Data AutoGluon automates machine learning tasks enabling you to easily achieve strong predictive performance in yo
Imagededup - 😎 Finding duplicate images made easy
imagededup is a python package that simplifies the task of finding exact and near duplicates in an image collection.
PySOT - SenseTime Research platform for single object tracking, implementing algorithms like SiamRPN and SiamMask.
PySOT is a software system designed by SenseTime Video Intelligence Research team. It implements state-of-the-art single object tracking algorit
NanoDet-Plus⚡Super fast and lightweight anchor-free object detection model. 🔥Only 980 KB(int8) / 1.8MB (fp16) and run 97FPS on cellphone🔥
NanoDet-Plus⚡Super fast and lightweight anchor-free object detection model. 🔥Only 980 KB(int8) / 1.8MB (fp16) and run 97FPS on cellphone🔥
Recurrent Neural Network Tutorial, Part 2 - Implementing a RNN in Python and Theano
Please read the blog post that goes with this code! Jupyter Notebook Setup System Requirements: Python, pip (Optional) virtualenv To start the Jupyter
Gans-in-action - Companion repository to GANs in Action: Deep learning with Generative Adversarial Networks
GANs in Action by Jakub Langr and Vladimir Bok List of available code: Chapter 2: Colab, Notebook Chapter 3: Notebook Chapter 4: Notebook Chapter 6: C
PConv-Keras - Unofficial implementation of "Image Inpainting for Irregular Holes Using Partial Convolutions". Try at: www.fixmyphoto.ai
Partial Convolutions for Image Inpainting using Keras Keras implementation of "Image Inpainting for Irregular Holes Using Partial Convolutions", https
TensorFlow-LiveLessons - "Deep Learning with TensorFlow" LiveLessons
TensorFlow-LiveLessons Note that the second edition of this video series is now available here. The second edition contains all of the content from th
Coursera - Quiz & Assignment of Coursera
Coursera Assignments This repository is aimed to help Coursera learners who have difficulties in their learning process. The quiz and programming home
Notes, programming assignments and quizzes from all courses within the Coursera Deep Learning specialization offered by deeplearning.ai
Coursera-deep-learning-specialization - Notes, programming assignments and quizzes from all courses within the Coursera Deep Learning specialization offered by deeplearning.ai: (i) Neural Networks and Deep Learning; (ii) Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization; (iii) Structuring Machine Learning Projects; (iv) Convolutional Neural Networks; (v) Sequence Models
PyTorch-Multi-Style-Transfer - Neural Style and MSG-Net
PyTorch-Style-Transfer This repo provides PyTorch Implementation of MSG-Net (ours) and Neural Style (Gatys et al. CVPR 2016), which has been included
Speech-Emotion-Analyzer - The neural network model is capable of detecting five different male/female emotions from audio speeches. (Deep Learning, NLP, Python)
Speech Emotion Analyzer The idea behind creating this project was to build a machine learning model that could detect emotions from the speech we have
Aws-machine-learning-university-accelerated-tab - Machine Learning University: Accelerated Tabular Data Class
Machine Learning University: Accelerated Tabular Data Class This repository contains slides, notebooks, and datasets for the Machine Learning Universi
Implementation of hyperparameter optimization/tuning methods for machine learning & deep learning models
Hyperparameter Optimization of Machine Learning Algorithms This code provides a hyper-parameter optimization implementation for machine learning algor
Nerf pl - NeRF (Neural Radiance Fields) and NeRF in the Wild using pytorch-lightning
nerf_pl Update: an improved NSFF implementation to handle dynamic scene is open! Update: NeRF-W (NeRF in the Wild) implementation is added to nerfw br
Python Deep Dive Course - Accompanying Materials
Python Deep Dive Various Jupyter notebooks and Python sources associated with my Udemy Python 3 Deep Dive course series: Part 1: Mainly functional pro
Books, Presentations, Workshops, Notebook Labs, and Model Zoo for Software Engineers and Data Scientists wanting to learn the TF.Keras Machine Learning framework
Books, Presentations, Workshops, Notebook Labs, and Model Zoo for Software Engineers and Data Scientists wanting to learn the TF.Keras Machine Learning framework
Keras Realtime Multi-Person Pose Estimation - Keras version of Realtime Multi-Person Pose Estimation project
This repository has become incompatible with the latest and recommended version of Tensorflow 2.0 Instead of refactoring this code painfully, I create
Finetune alexnet with tensorflow - Code for finetuning AlexNet in TensorFlow = 1.2rc0
Finetune AlexNet with Tensorflow Update 15.06.2016 I revised the entire code base to work with the new input pipeline coming with TensorFlow = versio
TensorFlow 101: Introduction to Deep Learning for Python Within TensorFlow
TensorFlow 101: Introduction to Deep Learning I have worked all my life in Machine Learning, and I've never seen one algorithm knock over its benchmar
Mememoji - A facial expression classification system that recognizes 6 basic emotions: happy, sad, surprise, fear, anger and neutral.
a project built with deep convolutional neural network and ❤️ Table of Contents Motivation The Database The Model 3.1 Input Layer 3.2 Convolutional La
Saliency - Framework-agnostic implementation for state-of-the-art saliency methods (XRAI, BlurIG, SmoothGrad, and more).
Saliency Methods 🔴 Now framework-agnostic! (Example core notebook) 🔴 🔗 For further explanation of the methods and more examples of the resulting ma
Fewshot-face-translation-GAN - Generative adversarial networks integrating modules from FUNIT and SPADE for face-swapping.
Few-shot face translation A GAN based approach for one model to swap them all. The table below shows our priliminary face-swapping results requiring o
Detectron2-FC a fast construction platform of neural network algorithm based on detectron2
What is Detectron2-FC Detectron2-FC a fast construction platform of neural network algorithm based on detectron2. We have been working hard in two dir
Intro-to-dl - Resources for "Introduction to Deep Learning" course.
Introduction to Deep Learning course resources https://www.coursera.org/learn/intro-to-deep-learning Running on Google Colab (tested for all weeks) Go
Video2x - A lossless video/GIF/image upscaler achieved with waifu2x, Anime4K, SRMD and RealSR.
Official Discussion Group (Telegram): https://t.me/video2x A Discord server is also available. Please note that most developers are only on Telegram.
A Tensorflow implementation of CapsNet based on Geoffrey Hinton's paper Dynamic Routing Between Capsules
CapsNet-Tensorflow A Tensorflow implementation of CapsNet based on Geoffrey Hinton's paper Dynamic Routing Between Capsules Notes: The current version
Client - 🔥 A tool for visualizing and tracking your machine learning experiments
Weights and Biases Use W&B to build better models faster. Track and visualize all the pieces of your machine learning pipeline, from datasets to produ
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation Created by Charles R. Qi, Hao Su, Kaichun Mo, Leonidas J. Guibas from Sta
Generate image analogies using neural matching and blending
neural image analogies This is basically an implementation of this "Image Analogies" paper, In our case, we use feature maps from VGG16. The patch mat
Tensorflow-Project-Template - A best practice for tensorflow project template architecture.
Tensorflow Project Template A simple and well designed structure is essential for any Deep Learning project, so after a lot of practice and contributi
Automatic library of congress classification, using word embeddings from book titles and synopses.
Automatic Library of Congress Classification The Library of Congress Classification (LCC) is a comprehensive classification system that was first deve
Public repository containing materials used for Feed Forward (FF) Neural Networks article.
Art041_NN_Feed_Forward Public repository containing materials used for Feed Forward (FF) Neural Networks article. -- Illustration of a very simple Fee
Simple-Neural-Network From Scratch in Python
Simple-Neural-Network From Scratch in Python This is a simple Neural Network created without any Machine Learning Libraries. The only dependencies are
Losslandscapetaxonomy - Taxonomizing local versus global structure in neural network loss landscapes
Taxonomizing local versus global structure in neural network loss landscapes Int
Cancer-and-Tumor-Detection-Using-Inception-model - In this repo i am gonna show you how i did cancer/tumor detection in lungs using deep neural networks, specifically here the Inception model by google.
Cancer-and-Tumor-Detection-Using-Inception-model In this repo i am gonna show you how i did cancer/tumor detection in lungs using deep neural networks
Patient-Survival - Using Python, I developed a Machine Learning model using classification techniques such as Random Forest and SVM classifiers to predict a patient's survival status that have undergone breast cancer surgery.
Patient-Survival - Using Python, I developed a Machine Learning model using classification techniques such as Random Forest and SVM classifiers to predict a patient's survival status that have undergone breast cancer surgery.
Omdena-abuja-anpd - Automatic Number Plate Detection for the security of lives and properties using Computer Vision.
Omdena-abuja-anpd - Automatic Number Plate Detection for the security of lives and properties using Computer Vision.
Time-series-deep-learning - Developing Deep learning LSTM, BiLSTM models, and NeuralProphet for multi-step time-series forecasting of stock price.
Stock Price Prediction Using Deep Learning Univariate Time Series Predicting stock price using historical data of a company using Neural networks for
Image-popularity-score - A novel deep regression method for image scoring.
Image-popularity-score - A novel deep regression method for image scoring.
BRNet - code for Automated assessment of BI-RADS categories for ultrasound images using multi-scale neural networks with an order-constrained loss function
BRNet code for "Automated assessment of BI-RADS categories for ultrasound images using multi-scale neural networks with an order-constrained loss func
Breast Cancer Detection 🔬 ITI "AI_Pro" Graduation Project
BreastCancerDetection - This program is designed to predict two severity of abnormalities associated with breast cancer cells: benign and malignant. Mammograms from MIAS is preprocessed and features are extracted using the pre-trained CNN.
CS5242_2021 - Neural Networks and Deep Learning, NUS CS5242, 2021
CS5242_2021 Neural Networks and Deep Learning, NUS CS5242, 2021 Cloud Machine #1 : Google Colab (Free GPU) Follow this Notebook installation : https:/
ADCS - Automatic Defect Classification System (ADCS) for SSMC
Table of Contents Table of Contents ADCS Overview Summary Operator's Guide Demo System Design System Logic Training Mode Production System Flow Folder
Locationinfo - A script helps the user to show network information such as ip address
Description This script helps the user to show network information such as ip ad
Siamese-nn-semantic-text-similarity - A repository containing comprehensive Neural Networks based PyTorch implementations for the semantic text similarity task
Siamese Deep Neural Networks for Semantic Text Similarity PyTorch A repository c
Ppq - A powerful offline neural network quantization tool with custimized IR
PPL Quantization Tool(PPL 量化工具) PPL Quantization Tool (PPQ) is a powerful offlin
HAR-stacked-residual-bidir-LSTMs - Deep stacked residual bidirectional LSTMs for HAR
HAR-stacked-residual-bidir-LSTM The project is based on this repository which is presented as a tutorial. It consists of Human Activity Recognition (H
Hyperopt for solving CIFAR-100 with a convolutional neural network (CNN) built with Keras and TensorFlow, GPU backend
Hyperopt for solving CIFAR-100 with a convolutional neural network (CNN) built with Keras and TensorFlow, GPU backend This project acts as both a tuto
Self Governing Neural Networks (SGNN): the Projection Layer
Self Governing Neural Networks (SGNN): the Projection Layer A SGNN's word projections preprocessing pipeline in scikit-learn In this notebook, we'll u
Neural-fractal - Create Fractals Using Complex-Valued Neural Networks!
Neural Fractal Create Fractals Using Complex-Valued Neural Networks! Home Page Features Define Dynamical Systems Using Complex-Valued Neural Networks
A Survey on Deep Learning Technique for Video Segmentation
A Survey on Deep Learning Technique for Video Segmentation A Survey on Deep Learning Technique for Video Segmentation Wenguan Wang, Tianfei Zhou, Fati
SOTA easy to use PyTorch-based DL training library
Easily train or fine-tune SOTA computer vision models from one training repository. SuperGradients Introduction Welcome to SuperGradients, a free open
Class-imbalanced / Long-tailed ensemble learning in Python. Modular, flexible, and extensible
IMBENS: Class-imbalanced Ensemble Learning in Python Language: English | Chinese/中文 Links: Documentation | Gallery | PyPI | Changelog | Source | Downl
“Robust Lightweight Facial Expression Recognition Network with Label Distribution Training”, AAAI 2021.
EfficientFace Zengqun Zhao, Qingshan Liu, Feng Zhou. "Robust Lightweight Facial Expression Recognition Network with Label Distribution Training". AAAI
PyTorch Lightning + Hydra. A feature-rich template for rapid, scalable and reproducible ML experimentation with best practices. ⚡🔥⚡
Lightning-Hydra-Template A clean and scalable template to kickstart your deep learning project 🚀 ⚡ 🔥 Click on Use this template to initialize new re
A library for uncertainty quantification based on PyTorch
Torchuq [logo here] TorchUQ is an extensive library for uncertainty quantification (UQ) based on pytorch. TorchUQ currently supports 10 representation
PyTorch Implementation of SSTNs for hyperspectral image classifications from the IEEE T-GRS paper "Spectral-Spatial Transformer Network for Hyperspectral Image Classification: A FAS Framework."
PyTorch Implementation of SSTN for Hyperspectral Image Classification Paper links: SSTN published on IEEE T-GRS. Also, you can directly find the imple
The model is designed to train a single and large neural network in order to predict correct translation by reading the given sentence.
Neural Machine Translation communication system The model is basically direct to convert one source language to another targeted language using encode
DeFi wallet on Chia Network.
DeFi wallet on Chia Network.
Bulk2Space is a spatial deconvolution method based on deep learning frameworks
Bulk2Space Spatially resolved single-cell deconvolution of bulk transcriptomes using Bulk2Space Bulk2Space is a spatial deconvolution method based on
TransPrompt - Towards an Automatic Transferable Prompting Framework for Few-shot Text Classification
TransPrompt This code is implement for our EMNLP 2021's paper 《TransPrompt:Towards an Automatic Transferable Prompting Framework for Few-shot Text Cla
Pytorch implementation of paper Semi-supervised Knowledge Transfer for Deep Learning from Private Training Data
Pytorch implementation of paper Semi-supervised Knowledge Transfer for Deep Learning from Private Training Data
A state-of-the-art semi-supervised method for image recognition
Mean teachers are better role models Paper ---- NIPS 2017 poster ---- NIPS 2017 spotlight slides ---- Blog post By Antti Tarvainen, Harri Valpola (The
Ladder network is a deep learning algorithm that combines supervised and unsupervised learning
This repository contains source code for the experiments in a paper titled Semi-Supervised Learning with Ladder Networks by A Rasmus, H Valpola, M Hon
Learning Dynamic Network Using a Reuse Gate Function in Semi-supervised Video Object Segmentation.
Training Script for Reuse-VOS This code implementation of CVPR 2021 paper : Learning Dynamic Network Using a Reuse Gate Function in Semi-supervised Vi
Weakly Supervised Learning of Instance Segmentation with Inter-pixel Relations, CVPR 2019 (Oral)
Weakly Supervised Learning of Instance Segmentation with Inter-pixel Relations The code of: Weakly Supervised Learning of Instance Segmentation with I