1588 Repositories
Python pre-trained-model Libraries
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
Python for downloading model data (HRRR, RAP, GFS, NBM, etc.) from NOMADS, NOAA's Big Data Program partners (Amazon, Google, Microsoft), and the University of Utah Pando Archive System.
Python for downloading model data (HRRR, RAP, GFS, NBM, etc.) from NOMADS, NOAA's Big Data Program partners (Amazon, Google, Microsoft), and the University of Utah Pando Archive System.
Research into Forex price prediction from price history using Deep Sequence Modeling with Stacked LSTMs.
Forex Data Prediction via Recurrent Neural Network Deep Sequence Modeling Research Paper Our research paper can be viewed here Installation Clone the
Official Implementation of "DialogLM: Pre-trained Model for Long Dialogue Understanding and Summarization."
DialogLM Code for AAAI 2022 paper: DialogLM: Pre-trained Model for Long Dialogue Understanding and Summarization. Pre-trained Models We release two ve
Code for Overinterpretation paper Overinterpretation reveals image classification model pathologies
Overinterpretation This repository contains the code for the paper: Overinterpretation reveals image classification model pathologies Authors: Brandon
A Physics-based Noise Formation Model for Extreme Low-light Raw Denoising (CVPR 2020 Oral & TPAMI 2021)
ELD The implementation of CVPR 2020 (Oral) paper "A Physics-based Noise Formation Model for Extreme Low-light Raw Denoising" and its journal (TPAMI) v
Trained T5 and T5-large model for creating keywords from text
text to keywords Trained T5-base and T5-large model for creating keywords from text. Supported languages: ru Pretraining Large version | Pretraining B
PyTorch GPU implementation of the ES-RNN model for time series forecasting
Fast ES-RNN: A GPU Implementation of the ES-RNN Algorithm A GPU-enabled version of the hybrid ES-RNN model by Slawek et al that won the M4 time-series
Analyzed the data of VISA applicants to build a predictive model to facilitate the process of VISA approvals.
Analyzed the data of Visa applicants, built a predictive model to facilitate the process of visa approvals, and based on important factors that significantly influence the Visa status recommended a suitable profile for the applicants for whom the visa should be certified or denied.
Sign Language Recognition service utilizing a deep learning model with Long Short-Term Memory to perform sign language recognition.
Sign Language Recognition Service This is a Sign Language Recognition service utilizing a deep learning model with Long Short-Term Memory to perform s
Adds timm pretrained backbone to pytorch's FasterRcnn model
timmFasterRcnn model_config.py - it returns the model,feat_sizes,output channel and the feat layer names, which is reqd by the Add_FPN.py file Add_FP
Cherche (search in French) allows you to create a neural search pipeline using retrievers and pre-trained language models as rankers.
Cherche (search in French) allows you to create a neural search pipeline using retrievers and pre-trained language models as rankers. Cherche is meant to be used with small to medium sized corpora. Cherche's main strength is its ability to build diverse and end-to-end pipelines.
Deepchecks is a Python package for comprehensively validating your machine learning models and data with minimal effort
Deepchecks is a Python package for comprehensively validating your machine learning models and data with minimal effort
General Assembly's 2015 Data Science course in Washington, DC
DAT8 Course Repository Course materials for General Assembly's Data Science course in Washington, DC (8/18/15 - 10/29/15). Instructor: Kevin Markham (
Largest list of models for Core ML (for iOS 11+)
Since iOS 11, Apple released Core ML framework to help developers integrate machine learning models into applications. The official documentation We'v
Official re-implementation of the Calibrated Adversarial Refinement model described in the paper Calibrated Adversarial Refinement for Stochastic Semantic Segmentation
Official re-implementation of the Calibrated Adversarial Refinement model described in the paper Calibrated Adversarial Refinement for Stochastic Semantic Segmentation
Seasonal Contrast: Unsupervised Pre-Training from Uncurated Remote Sensing Data
Seasonal Contrast: Unsupervised Pre-Training from Uncurated Remote Sensing Data This is the official PyTorch implementation of the SeCo paper: @articl
The implementation of the lifelong infinite mixture model
Lifelong infinite mixture model 📋 This is the implementation of the Lifelong infinite mixture model 📋 Accepted by ICCV 2021 Title : Lifelong Infinit
deep learning model with only python and numpy with test accuracy 99 % on mnist dataset and different optimization choices
deep_nn_model_with_only_python_100%_test_accuracy deep learning model with only python and numpy with test accuracy 99 % on mnist dataset and differen
Django CMS Project for quicksetup with minimal installation process.
Django CMS Project for quicksetup with minimal installation process.
EfficientMPC - Efficient Model Predictive Control Implementation
efficientMPC Efficient Model Predictive Control Implementation The original algo
ShortenURL-model - The model layer class for shorten url service
ShortenURL Model The model layer class for shorten URL service Usage Complete th
PyExplainer: A Local Rule-Based Model-Agnostic Technique (Explainable AI)
PyExplainer PyExplainer is a local rule-based model-agnostic technique for generating explanations (i.e., why a commit is predicted as defective) of J
Bottom-up attention model for image captioning and VQA, based on Faster R-CNN and Visual Genome
bottom-up-attention This code implements a bottom-up attention model, based on multi-gpu training of Faster R-CNN with ResNet-101, using object and at
Real-time face detection and emotion/gender classification using fer2013/imdb datasets with a keras CNN model and openCV.
Real-time face detection and emotion/gender classification using fer2013/imdb datasets with a keras CNN model and openCV.
Code for the paper "Jukebox: A Generative Model for Music"
Status: Archive (code is provided as-is, no updates expected) Jukebox Code for "Jukebox: A Generative Model for Music" Paper Blog Explorer Colab Insta
This project deals with a simplified version of a more general problem of Aspect Based Sentiment Analysis.
Aspect_Based_Sentiment_Extraction Created on: 5th Jan, 2022. This project deals with an important field of Natural Lnaguage Processing - Aspect Based
Iris prediction model is used to classify iris species created julia's DecisionTree, DataFrames, JLD2, PlotlyJS and Statistics packages.
Iris Species Predictor Iris prediction is used to classify iris species using their sepal length, sepal width, petal length and petal width created us
This code is 3d-CNN model that can predict environmental value
Predict-environmental-value-3dCNN This code is 3d-CNN model that can predict environmental value. Firstly, I built a model that can create a lot of bu
An interactive DNN Model deployed on web that predicts the chance of heart failure for a patient with an accuracy of 98%
Heart Failure Predictor About A Web UI deployed Dense Neural Network Model Made using Tensorflow that predicts whether the patient is healthy or has c
Simple web app example serving a PyTorch model using streamlit and FastAPI
streamlit-fastapi-model-serving Simple example of usage of streamlit and FastAPI for ML model serving described on this blogpost and PyConES 2020 vide
Reinforcement learning algorithms in RLlib
raylab Reinforcement learning algorithms in RLlib and PyTorch. Installation pip install raylab Quickstart Raylab provides agents and environments to b
This MVP data web app uses the Streamlit framework and Facebook's Prophet forecasting package to generate a dynamic forecast from your own data.
📈 Automated Time Series Forecasting Background: This MVP data web app uses the Streamlit framework and Facebook's Prophet forecasting package to gene
GPT-2 Model for Leetcode Questions in python
Leetcode using AI 🤖 GPT-2 Model for Leetcode Questions in python New demo here: https://huggingface.co/spaces/gagan3012/project-code-py Note: the Ans
Honor's thesis project analyzing whether the GPT-2 model can more effectively generate free-verse or structured poetry.
gpt2-poetry The following code is for my senior honor's thesis project, under the guidance of Dr. Keith Holyoak at the University of California, Los A
Pytorch implementation of the popular Improv RNN model originally proposed by the Magenta team.
Pytorch Implementation of Improv RNN Overview This code is a pytorch implementation of the popular Improv RNN model originally implemented by the Mage
Benchmarks for Model-Based Optimization
Design-Bench Design-Bench is a benchmarking framework for solving automatic design problems that involve choosing an input that maximizes a black-box
Fast Learning of MNL Model From General Partial Rankings with Application to Network Formation Modeling
Fast-Partial-Ranking-MNL This repo provides a PyTorch implementation for the CopulaGNN models as described in the following paper: Fast Learning of MN
Code, pre-trained models and saliency results for the paper "Boosting RGB-D Saliency Detection by Leveraging Unlabeled RGB Images".
Boosting RGB-D Saliency Detection by Leveraging Unlabeled RGB This repository is the official implementation of the paper. Our results comming soon in
This repository provides some of the code implemented and the data used for the work proposed in "A Cluster-Based Trip Prediction Graph Neural Network Model for Bike Sharing Systems".
cluster-link-prediction This repository provides some of the code implemented and the data used for the work proposed in "A Cluster-Based Trip Predict
CV backbones including GhostNet, TinyNet and TNT, developed by Huawei Noah's Ark Lab.
CV Backbones including GhostNet, TinyNet, TNT (Transformer in Transformer) developed by Huawei Noah's Ark Lab. GhostNet Code TinyNet Code TNT Code Pyr
ESMAC diags - Earth System Model Aerosol-Cloud Diagnostics Package
Earth System Model Aerosol-Cloud Diagnostics Package This Earth System Model (ES
CoMoGAN: continuous model-guided image-to-image translation. CVPR 2021 oral.
CoMoGAN: Continuous Model-guided Image-to-Image Translation Official repository. Paper CoMoGAN: continuous model-guided image-to-image translation [ar
An Unpaired Sketch-to-Photo Translation Model
Unpaired-Sketch-to-Photo-Translation We have released our code at https://github.com/rt219/Unsupervised-Sketch-to-Photo-Synthesis This project is the
UI2I via StyleGAN2 - Unsupervised image-to-image translation method via pre-trained StyleGAN2 network
We proposed an unsupervised image-to-image translation method via pre-trained StyleGAN2 network. paper: Unsupervised Image-to-Image Translation via Pr
Net2net - Network-to-Network Translation with Conditional Invertible Neural Networks
Net2Net Code accompanying the NeurIPS 2020 oral paper Network-to-Network Translation with Conditional Invertible Neural Networks Robin Rombach*, Patri
AttentionGAN for Unpaired Image-to-Image Translation & Multi-Domain Image-to-Image Translation
AttentionGAN-v2 for Unpaired Image-to-Image Translation AttentionGAN-v2 Framework The proposed generator learns both foreground and background attenti
A unified framework to jointly model images, text, and human attention traces.
connect-caption-and-trace This repository contains the reference code for our paper Connecting What to Say With Where to Look by Modeling Human Attent
LaBERT - A length-controllable and non-autoregressive image captioning model.
Length-Controllable Image Captioning (ECCV2020) This repo provides the implemetation of the paper Length-Controllable Image Captioning. Install conda
Moer Grounded Image Captioning by Distilling Image-Text Matching Model
Moer Grounded Image Captioning by Distilling Image-Text Matching Model Requirements Python 3.7 Pytorch 1.2 Prepare data Please use git clone --recurse
DCGAN-tensorflow - A tensorflow implementation of Deep Convolutional Generative Adversarial Networks
DCGAN in Tensorflow Tensorflow implementation of Deep Convolutional Generative Adversarial Networks which is a stabilize Generative Adversarial Networ
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
Tensorflow implementation of soft-attention mechanism for video caption generation.
SA-tensorflow Tensorflow implementation of soft-attention mechanism for video caption generation. An example of soft-attention mechanism. The attentio
DeepSpeech - Easy-to-use Speech Toolkit including SOTA ASR pipeline, influential TTS with text frontend and End-to-End Speech Simultaneous Translation.
(简体中文|English) Quick Start | Documents | Models List PaddleSpeech is an open-source toolkit on PaddlePaddle platform for a variety of critical tasks i
Preprossing-loan-data-with-NumPy - In this project, I have cleaned and pre-processed the loan data that belongs to an affiliate bank based in the United States.
Preprossing-loan-data-with-NumPy In this project, I have cleaned and pre-processed the loan data that belongs to an affiliate bank based in the United
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
Lending-Club-Loans - Using TensorFlow to create an ANN model to predict whether people would charge off or pay back their loans.
Lending Club Loans: Brief Introduction LendingClub is a US peer-to-peer lending company, headquartered in San Francisco, California.[3] It was the fir
Churn-Prediction-Project - In this project, a churn prediction model is developed for a private bank as a term project for Data Mining class.
Churn-Prediction-Project In this project, a churn prediction model is developed for a private bank as a term project for Data Mining class. Project in
PenguinSpeciesPredictionML - Basic model to predict Penguin species based on beak size and sex.
Penguin Species Prediction (ML) 🐧 👨🏽💻 What? 💻 This project is a basic model using sklearn methods to predict Penguin species based on beak size
DGN pymarl - Implementation of DGN on Pymarl, which could be trained by VDN or QMIX
This is the implementation of DGN on Pymarl, which could be trained by VDN or QM
Stroke-predictions-ml-model - Machine learning model to predict individuals chances of having a stroke
stroke-predictions-ml-model machine learning model to predict individuals chance
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.
Pytorch-3dunet - 3D U-Net model for volumetric semantic segmentation written in pytorch
pytorch-3dunet PyTorch implementation 3D U-Net and its variants: Standard 3D U-Net based on 3D U-Net: Learning Dense Volumetric Segmentation from Spar
Got-book-6 - LSTM trained on the first five ASOIAF/GOT books
GOT Book 6 Generator Are you tired of waiting for the next GOT book to come out? I know that I am, which is why I decided to train a RNN on the first
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
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🔥
Tensorflow solution of NER task Using BiLSTM-CRF model with Google BERT Fine-tuning And private Server services
Tensorflow solution of NER task Using BiLSTM-CRF model with Google BERT Fine-tuning
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
KoBERT - Korean BERT pre-trained cased (KoBERT)
KoBERT KoBERT Korean BERT pre-trained cased (KoBERT) Why'?' Training Environment Requirements How to install How to use Using with PyTorch Using with
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
Captcha-tensorflow - Image Captcha Solving Using TensorFlow and CNN Model. Accuracy 90%+
Captcha Solving Using TensorFlow Introduction Solve captcha using TensorFlow. Learn CNN and TensorFlow by a practical project. Follow the steps, run t
Modified prey-predator system - Modified prey–predator model describes the rate of change for each species by adding coupling terms.
Modified prey-predator system We aim to study the behaviors of the modified prey–predator model and establish the effects of several parameters that p
Linescanning - Package for (pre)processing of anatomical and (linescanning) fMRI data
line scanning repository This repository contains all of the tools used during the acquisition and postprocessing of line scanning data at the Spinoza
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.
Price-Prediction-For-a-Dream-Home - A machine learning based linear regression trained model for house price prediction.
Price-Prediction-For-a-Dream-Home ROADMAP TO THIS LINEAR REGRESSION BASED HOUSE PRICE PREDICTION PREDICTION MODEL Import all the dependencies of the p
Iris-Heroku - Putting a Machine Learning Model into Production with Flask and Heroku
Puesta en Producción de un modelo de aprendizaje automático con Flask y Heroku L
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
View model summaries in PyTorch!
torchinfo (formerly torch-summary) Torchinfo provides information complementary to what is provided by print(your_model) in PyTorch, similar to Tensor
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
🌀 Pykka makes it easier to build concurrent applications.
🌀 Pykka Pykka makes it easier to build concurrent applications. Pykka is a Python implementation of the actor model. The actor model introduces some
A Probabilistic End-To-End Task-Oriented Dialog Model with Latent Belief States towards Semi-Supervised Learning
LABES This is the code for EMNLP 2020 paper "A Probabilistic End-To-End Task-Oriented Dialog Model with Latent Belief States towards Semi-Supervised L
Neural network sequence labeling model
Sequence labeler This is a neural network sequence labeling system. Given a sequence of tokens, it will learn to assign labels to each token. Can be u
PyTorch implementation of the Flow Gaussian Mixture Model (FlowGMM) model from our paper
Flow Gaussian Mixture Model (FlowGMM) This repository contains a PyTorch implementation of the Flow Gaussian Mixture Model (FlowGMM) model from our pa
Semi-supervised Adversarial Learning to Generate Photorealistic Face Images of New Identities from 3D Morphable Model
Semi-supervised Adversarial Learning to Generate Photorealistic Face Images of New Identities from 3D Morphable Model Baris Gecer 1, Binod Bhattarai 1
Keras implementation of the GNM model in paper ’Graph-Based Semi-Supervised Learning with Nonignorable Nonresponses‘
Graph-based joint model with Nonignorable Missingness (GNM) This is a Keras implementation of the GNM model in paper ’Graph-Based Semi-Supervised Lear
PyTorch implementation for Graph Contrastive Learning with Augmentations
Graph Contrastive Learning with Augmentations PyTorch implementation for Graph Contrastive Learning with Augmentations [poster] [appendix] Yuning You*
CCCL: Contrastive Cascade Graph Learning.
CCGL: Contrastive Cascade Graph Learning This repo provides a reference implementation of Contrastive Cascade Graph Learning (CCGL) framework as descr
Aerospace utilities: flight conditions package, standard atmosphere model, and more.
Aerospace Utilities About Module that contains commonly-used aerospace utilities for problem solving. Flight Condition: input altitude to compute comm
In this project, two programs can help you take full agvantage of time on the model training with a remote server
In this project, two programs can help you take full agvantage of time on the model training with a remote server, which can push notification to your phone about the information during model training, like the model indices and unexpected interrupts. Then you can do something in time for your work.
GCC: Graph Contrastive Coding for Graph Neural Network Pre-Training @ KDD 2020
GCC: Graph Contrastive Coding for Graph Neural Network Pre-Training Original implementation for paper GCC: Graph Contrastive Coding for Graph Neural N
Pytorch implementation of the paper "COAD: Contrastive Pre-training with Adversarial Fine-tuning for Zero-shot Expert Linking."
Expert-Linking Pytorch implementation of the paper "COAD: Contrastive Pre-training with Adversarial Fine-tuning for Zero-shot Expert Linking." This is
A curated list of awesome Model-Based RL resources
Awesome Model-Based Reinforcement Learning This is a collection of research papers for model-based reinforcement learning (mbrl). And the repository w
Scalable and Elastic Deep Reinforcement Learning Using PyTorch. Please star. 🔥
ElegantRL “小雅”: Scalable and Elastic Deep Reinforcement Learning ElegantRL is developed for researchers and practitioners with the following advantage
Bianace Prediction Pytorch Model
Bianace Prediction Pytorch Model Main Results ETHUSDT from 2021-01-01 00:00:00 t
Model synchronization from dbt to Metabase.
dbt-metabase Model synchronization from dbt to Metabase. If dbt is your source of truth for database schemas and you use Metabase as your analytics to
This Jupyter notebook shows one way to implement a simple first-order low-pass filter on sampled data in discrete time.
How to Implement a First-Order Low-Pass Filter in Discrete Time We often teach or learn about filters in continuous time, but then need to implement t
Library for managing git hooks
Autohooks Library for managing and writing git hooks in Python. Looking for automatic formatting or linting, e.g., with black and pylint, while creati
A Python reference implementation of the CF data model
cfdm A Python reference implementation of the CF data model. References Compliance with FAIR principles Documentation https://ncas-cms.github.io/cfdm
A simple model based API maker written in Python and based on Django and Django REST Framework
Fast DRF Fast DRF is a small library for making API faster with Django and Django REST Framework. It's easy and configurable. Full Documentation here