5604 Repositories
Python self-supervised-learning Libraries
Jupyter Notebook tutorials on solving real-world problems with Machine Learning & Deep Learning using PyTorch
Jupyter Notebook tutorials on solving real-world problems with Machine Learning & Deep Learning using PyTorch. Topics: Face detection with Detectron 2, Time Series anomaly detection with LSTM Autoencoders, Object Detection with YOLO v5, Build your first Neural Network, Time Series forecasting for Coronavirus daily cases, Sentiment Analysis with BERT.
Koç University deep learning framework.
Knet Knet (pronounced "kay-net") is the Koç University deep learning framework implemented in Julia by Deniz Yuret and collaborators. It supports GPU
Setup and customize deep learning environment in seconds.
Deepo is a series of Docker images that allows you to quickly set up your deep learning research environment supports almost all commonly used deep le
Hide screen when boss is approaching.
BossSensor Hide your screen when your boss is approaching. Demo The boss stands up. He is approaching. When he is approaching, the program fetches fac
The best free and open-source automated time tracker. Cross-platform, extensible, privacy-focused.
Records what you do so that you can know how you've spent your time. All in a secure way where you control the data. Website — Forum — Documentation —
Anomaly detection related books, papers, videos, and toolboxes
Anomaly Detection Learning Resources Outlier Detection (also known as Anomaly Detection) is an exciting yet challenging field, which aims to identify
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
Distributed deep learning on Hadoop and Spark clusters.
Note: we're lovingly marking this project as Archived since we're no longer supporting it. You are welcome to read the code and fork your own version
My solution to the book A Collection of Data Science Take-Home Challenges
DS-Take-Home Solution to the book "A Collection of Data Science Take-Home Challenges". Note: Please don't contact me for the dataset. This repository
Official PyTorch implementation of "Dual Path Learning for Domain Adaptation of Semantic Segmentation".
Dual Path Learning for Domain Adaptation of Semantic Segmentation Official PyTorch implementation of "Dual Path Learning for Domain Adaptation of Sema
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
Official repository for "Orthogonal Projection Loss" (ICCV'21)
Orthogonal Projection Loss (ICCV'21) Kanchana Ranasinghe, Muzammal Naseer, Munawar Hayat, Salman Khan, & Fahad Shahbaz Khan Paper Link | Project Page
Learning with Noisy Labels via Sparse Regularization, ICCV2021
Learning with Noisy Labels via Sparse Regularization This repository is the official implementation of [Learning with Noisy Labels via Sparse Regulari
Code for "Learning Skeletal Graph Neural Networks for Hard 3D Pose Estimation" ICCV'21
Skeletal-GNN Code for "Learning Skeletal Graph Neural Networks for Hard 3D Pose Estimation" ICCV'21 Various deep learning techniques have been propose
Python3 / PyTorch implementation of the following paper: Fine-grained Semantics-aware Representation Enhancement for Self-supervisedMonocular Depth Estimation. ICCV 2021 (oral)
FSRE-Depth This is a Python3 / PyTorch implementation of FSRE-Depth, as described in the following paper: Fine-grained Semantics-aware Representation
Implementation of Cross-category Video Highlight Detection via Set-based Learning (ICCV 2021).
Cross-category Video Highlight Detection via Set-based Learning Introduction This project is an implementation of ``Cross-category Video Highlight Det
Foreground-Action Consistency Network for Weakly Supervised Temporal Action Localization
FAC-Net Foreground-Action Consistency Network for Weakly Supervised Temporal Action Localization Linjiang Huang (CUHK), Liang Wang (CASIA), Hongsheng
Train Scene Graph Generation for Visual Genome and GQA in PyTorch = 1.2 with improved zero and few-shot generalization.
Scene Graph Generation Object Detections Ground truth Scene Graph Generated Scene Graph In this visualization, woman sitting on rock is a zero-shot tr
PyTorch implementation of paper "MT-ORL: Multi-Task Occlusion Relationship Learning" (ICCV 2021)
MT-ORL: Multi-Task Occlusion Relationship Learning Official implementation of paper "MT-ORL: Multi-Task Occlusion Relationship Learning" (ICCV 2021) P
Resco: A simple python package that report the effect of deep residual learning
resco Description resco is a simple python package that report the effect of dee
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
Code and Experiments for ACL-IJCNLP 2021 Paper Mind Your Outliers! Investigating the Negative Impact of Outliers on Active Learning for Visual Question Answering.
Code and Experiments for ACL-IJCNLP 2021 Paper Mind Your Outliers! Investigating the Negative Impact of Outliers on Active Learning for Visual Question Answering.
This is the code of paper ``Contrastive Coding for Active Learning under Class Distribution Mismatch'' with python.
Contrastive Coding for Active Learning under Class Distribution Mismatch Official PyTorch implementation of ["Contrastive Coding for Active Learning u
Source code for Task-Aware Variational Adversarial Active Learning
Task-Aware Variational Adversarial Active Learning - Official Pytorch implementation of the CVPR 2021 paper Kwanyoung Kim, Dongwon Park, Kwang In Kim,
Sequential GCN for Active Learning
Sequential GCN for Active Learning Please cite if using the code: Link to paper. Requirements: python 3.6+ torch 1.0+ pip libraries: tqdm, sklearn, sc
Code for the paper "Can Active Learning Preemptively Mitigate Fairness Issues?" presented at RAI 2021.
Can Active Learning Preemptively Mitigate Fairness Issues? Code for the paper "Can Active Learning Preemptively Mitigate Fairness Issues?" presented a
State-Relabeling Adversarial Active Learning
State-Relabeling Adversarial Active Learning Code for SRAAL [2020 CVPR Oral] Requirements torch = 1.6.0 numpy = 1.19.1 tqdm = 4.31.1 AL Results The
An implementation of the BADGE batch active learning algorithm.
Batch Active learning by Diverse Gradient Embeddings (BADGE) An implementation of the BADGE batch active learning algorithm. Details are provided in o
Code for the paper "Reinforced Active Learning for Image Segmentation"
Reinforced Active Learning for Image Segmentation (RALIS) Code for the paper Reinforced Active Learning for Image Segmentation Dependencies python 3.6
A curated list of awesome Active Learning
Awesome Active Learning 🤩 A curated list of awesome Active Learning ! 🤩 Background (image source: Settles, Burr) What is Active Learning? Active lea
python 93% acc. CNN Dogs Vs Cats ( Pytorch )
English | 简体中文(测试中...敬请期待) Cnn-Classification-Dog-Vs-Cat 猫狗辨别 (pytorch版本) CNN Resnet18 的猫狗分类器,基于ResNet及其变体网路系列,对于一般的图像识别任务表现优异,模型精准度高达93%(小型样本)。 项目制作于
A library for graph deep learning research
Documentation | Paper [JMLR] | Tutorials | Benchmarks | Examples DIG: Dive into Graphs is a turnkey library for graph deep learning research. Why DIG?
Predico Disease Prediction system based on symptoms provided by patient- using Python-Django & Machine Learning
Predico Disease Prediction system based on symptoms provided by patient- using Python-Django & Machine Learning
MNE: Magnetoencephalography (MEG) and Electroencephalography (EEG) in Python
MNE-Python MNE-Python software is an open-source Python package for exploring, visualizing, and analyzing human neurophysiological data such as MEG, E
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
make ASCII Art by Deep Learning
DeepAA This is convolutional neural networks generating ASCII art. This repository is under construction. This work is accepted by NIPS 2017 Workshop,
Python Client for Algorithmia Algorithms and Data API
Algorithmia Common Library (python) Python client library for accessing the Algorithmia API For API documentation, see the PythonDocs Algorithm Develo
Forum written for learning purposes in flask and sqlalchemy
Flask-forum forum written for learning purposes using SQLalchemy and flask How to install install requirements pip install sqlalchemy flask clone repo
A Python Package For System Identification Using NARMAX Models
SysIdentPy is a Python module for System Identification using NARMAX models built on top of numpy and is distributed under the 3-Clause BSD license. N
BigDL - Evaluate the performance of BigDL (Distributed Deep Learning on Apache Spark) in big data analysis problems
Evaluate the performance of BigDL (Distributed Deep Learning on Apache Spark) in big data analysis problems.
Machine Learning Study 혼자 해보기
Machine Learning Study 혼자 해보기 기여자 (Contributors) ✨ Teddy Lee 🏠 HongJaeKwon 🏠 Seungwoo Han 🏠 Tae Heon Kim 🏠 Steve Kwon 🏠 SW Song 🏠 K1A2 🏠 Wooil
Code repo for the book "Feature Engineering for Machine Learning," by Alice Zheng and Amanda Casari, O'Reilly 2018
feature-engineering-book This repo accompanies "Feature Engineering for Machine Learning," by Alice Zheng and Amanda Casari. O'Reilly, 2018. The repo
Advbox is a toolbox to generate adversarial examples that fool neural networks in PaddlePaddle、PyTorch、Caffe2、MxNet、Keras、TensorFlow and Advbox can benchmark the robustness of machine learning models.
Advbox is a toolbox to generate adversarial examples that fool neural networks in PaddlePaddle、PyTorch、Caffe2、MxNet、Keras、TensorFlow and Advbox can benchmark the robustness of machine learning models. Advbox give a command line tool to generate adversarial examples with Zero-Coding.
Official Repsoitory for "Mish: A Self Regularized Non-Monotonic Neural Activation Function" [BMVC 2020]
Mish: Self Regularized Non-Monotonic Activation Function BMVC 2020 (Official Paper) Notes: (Click to expand) A considerably faster version based on CU
Rainbow is all you need! A step-by-step tutorial from DQN to Rainbow
Do you want a RL agent nicely moving on Atari? Rainbow is all you need! This is a step-by-step tutorial from DQN to Rainbow. Every chapter contains bo
Machine Learning in Asset Management (by @firmai)
Machine Learning in Asset Management If you like this type of content then visit ML Quant site below: https://www.ml-quant.com/ Part One Follow this l
Pytorch implementations of Bayes By Backprop, MC Dropout, SGLD, the Local Reparametrization Trick, KF-Laplace, SG-HMC and more
Bayesian Neural Networks Pytorch implementations for the following approximate inference methods: Bayes by Backprop Bayes by Backprop + Local Reparame
The official code repository for examples in the O'Reilly book 'Generative Deep Learning'
Generative Deep Learning Teaching Machines to paint, write, compose and play The official code repository for examples in the O'Reilly book 'Generativ
Machine Learning University: Accelerated Computer Vision Class
Machine Learning University: Accelerated Computer Vision Class This repository contains slides, notebooks, and datasets for the Machine Learning Unive
Face Mask Detection system based on computer vision and deep learning using OpenCV and Tensorflow/Keras
Face Mask Detection Face Mask Detection System built with OpenCV, Keras/TensorFlow using Deep Learning and Computer Vision concepts in order to detect
Keras implementation of "One pixel attack for fooling deep neural networks" using differential evolution on Cifar10 and ImageNet
One Pixel Attack How simple is it to cause a deep neural network to misclassify an image if an attacker is only allowed to modify the color of one pix
🏖 Keras Implementation of Painting outside the box
Keras implementation of Image OutPainting This is an implementation of Painting Outside the Box: Image Outpainting paper from Standford University. So
Vehicle detection using machine learning and computer vision techniques for Udacity's Self-Driving Car Engineer Nanodegree.
Vehicle Detection Video demo Overview Vehicle detection using these machine learning and computer vision techniques. Linear SVM HOG(Histogram of Orien
Quilt is a self-organizing data hub for S3
Quilt is a self-organizing data hub Python Quick start, tutorials If you have Python and an S3 bucket, you're ready to create versioned datasets with
DL course co-developed by YSDA, HSE and Skoltech
Deep learning course This repo supplements Deep Learning course taught at YSDA and HSE @fall'21. For previous iteration visit the spring21 branch. Lec
Full Stack Deep Learning Labs
Full Stack Deep Learning Labs Welcome! Project developed during lab sessions of the Full Stack Deep Learning Bootcamp. We will build a handwriting rec
Implementations of CNNs, RNNs, GANs, etc
Tensorflow Programs and Tutorials This repository will contain Tensorflow tutorials on a lot of the most popular deep learning concepts. It'll also co
This repository contains small projects related to Neural Networks and Deep Learning in general.
ILearnDeepLearning.py Description People say that nothing develops and teaches you like getting your hands dirty. This repository contains small proje
A collection of Reinforcement Learning algorithms from Sutton and Barto's book and other research papers implemented in Python.
Reinforcement-Learning-Notebooks A collection of Reinforcement Learning algorithms from Sutton and Barto's book and other research papers implemented
NeuralTalk is a Python+numpy project for learning Multimodal Recurrent Neural Networks that describe images with sentences.
#NeuralTalk Warning: Deprecated. Hi there, this code is now quite old and inefficient, and now deprecated. I am leaving it on Github for educational p
This is a Tensorflow implementation of Learning to See in the Dark in CVPR 2018
Learning-to-See-in-the-Dark This is a Tensorflow implementation of Learning to See in the Dark in CVPR 2018, by Chen Chen, Qifeng Chen, Jia Xu, and Vl
TensorFlow implementation of AlexNet and its training and testing on ImageNet ILSVRC 2012 dataset
AlexNet training on ImageNet LSVRC 2012 This repository contains an implementation of AlexNet convolutional neural network and its training and testin
IRON Kaggle project done while doing IRONHACK Bootcamp where we had to analyze and use a Machine Learning Project to predict future sales
IRON Kaggle project done while doing IRONHACK Bootcamp where we had to analyze and use a Machine Learning Project to predict future sales. In this case, we ended up using XGBoost because it was the one with a higher score and less overfitting.
Code for NeurIPS 2021 paper: Invariant Causal Imitation Learning for Generalizable Policies
Invariant Causal Imitation Learning for Generalizable Policies Ioana Bica, Daniel Jarrett, Mihaela van der Schaar Neural Information Processing System
A discord self-bot to automate shitposting for your everyday needs.
Shitpost Selfbot A discord self-bot to automate shitposting for your everyday needs. Caution: May be a little racist. I have no clue where we are taki
An AI made using artificial intelligence (AI) and machine learning algorithms (ML) .
DTech.AIML An AI made using artificial intelligence (AI) and machine learning algorithms (ML) . This is created by help of some members in my team and
Crunchdao - Python API for the Crunchdao machine learning tournament
Python API for the Crunchdao machine learning tournament Interact with the Crunc
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
K-Means Clustering and Hierarchical Clustering Unsupervised Learning Solution in Python3.
Unsupervised Learning - K-Means Clustering and Hierarchical Clustering - The Heritage Foundation's Economic Freedom Index Analysis 2019 - By David Sal
Code for paper "Multi-level Disentanglement Graph Neural Network"
Multi-level Disentanglement Graph Neural Network (MD-GNN) This is a PyTorch implementation of the MD-GNN, and the code includes the following modules:
Its a Plant Leaf Disease Detection System based on Machine Learning.
My_Project_Code Its a Plant Leaf Disease Detection System based on Machine Learning. I have used Tomato Leaves Dataset from kaggle. This system detect
Coinloggr - A learning resource and social platform for the coin collecting community
Coinloggr A learning resource and social platform for the coin collecting commun
Multi-Modal Machine Learning toolkit based on PaddlePaddle.
简体中文 | English PaddleMM 简介 飞桨多模态学习工具包 PaddleMM 旨在于提供模态联合学习和跨模态学习算法模型库,为处理图片文本等多模态数据提供高效的解决方案,助力多模态学习应用落地。 近期更新 2022.1.5 发布 PaddleMM 初始版本 v1.0 特性 丰富的任务
RLMeta is a light-weight flexible framework for Distributed Reinforcement Learning Research.
RLMeta rlmeta - a flexible lightweight research framework for Distributed Reinforcement Learning based on PyTorch and moolib Installation To build fro
🚀 An end-to-end ML applications using PyTorch, W&B, FastAPI, Docker, Streamlit and Heroku
🚀 An end-to-end ML applications using PyTorch, W&B, FastAPI, Docker, Streamlit and Heroku
Go from graph data to a secure and interactive visual graph app in 15 minutes. Batteries-included self-hosting of graph data apps with Streamlit, Graphistry, RAPIDS, and more!
✔️ Linux ✔️ OS X ❌ Windows (#39) Welcome to graph-app-kit Turn your graph data into a secure and interactive visual graph app in 15 minutes! Why This
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
Serve TensorFlow ML models with TF-Serving and then create a Streamlit UI to use them
TensorFlow Serving + Streamlit! ✨ 🖼️ Serve TensorFlow ML models with TF-Serving and then create a Streamlit UI to use them! This is a pretty simple S
Repository for Project Insight: NLP as a Service
Project Insight NLP as a Service Contents Introduction Features Installation Setup and Documentation Project Details Demonstration Directory Details H
A Streamlit web app that generates Rick and Morty stories using GPT2.
Rick and Morty Story Generator This project uses a pre-trained GPT2 model, which was fine-tuned on Rick and Morty transcripts, to generate new stories
An image classification app boilerplate to serve your deep learning models asap!
Image 🖼 Classification App Boilerplate Have you been puzzled by tons of videos, blogs and other resources on the internet and don't know where and ho
Computer Vision application in the web
Computer Vision application in the web Preview Usage Clone this repo git clone https://github.com/amineHY/WebApp-Computer-Vision-streamlit.git cd Web
An open-source project for applying deep learning to medical scenarios
Auto Vaidya An open source solution for creating end-end web app for employing the power of deep learning in various clinical scenarios like implant d
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
Powering up Apache JMeter with Streamlit and opening the door for machine learning.
Powering up Apache JMeter with Streamlit Overview Apache JMeter is an open source load testing tool written in 100% pure Java. JMeter supports umpteen
👑 spaCy building blocks and visualizers for Streamlit apps
spacy-streamlit: spaCy building blocks for Streamlit apps This package contains utilities for visualizing spaCy models and building interactive spaCy-
Streamlit app demonstrating an image browser for the Udacity self-driving-car dataset with realtime object detection using YOLO.
Streamlit Demo: The Udacity Self-driving Car Image Browser This project demonstrates the Udacity self-driving-car dataset and YOLO object detection in
Self sustained producer-consumer(prosumer) policy study using Python and Gurobi
Prosumer Policy This project aims to model the optimum dispatch behaviour of households with PV and battery systems under different policy instrument
Multi-Modal Machine Learning toolkit based on PyTorch.
简体中文 | English TorchMM 简介 多模态学习工具包 TorchMM 旨在于提供模态联合学习和跨模态学习算法模型库,为处理图片文本等多模态数据提供高效的解决方案,助力多模态学习应用落地。 近期更新 2022.1.5 发布 TorchMM 初始版本 v1.0 特性 丰富的任务场景:工具
Real-time LIDAR-based Urban Road and Sidewalk detection for Autonomous Vehicles 🚗
urban_road_filter: a real-time LIDAR-based urban road and sidewalk detection algorithm for autonomous vehicles Dependency ROS (tested with Kinetic and
Machine learning library for fast and efficient Gaussian mixture models
This repository contains code which implements the Stochastic Gaussian Mixture Model (S-GMM) for event-based datasets Dependencies CMake Premake4 Blaz
DeepSpamReview: Detection of Fake Reviews on Online Review Platforms using Deep Learning Architectures. Summer Internship project at CoreView Systems.
Detection of Fake Reviews on Online Review Platforms using Deep Learning Architectures Dataset: https://s3.amazonaws.com/fast-ai-nlp/yelp_review_polar
Multi-Objective Reinforced Active Learning
Multi-Objective Reinforced Active Learning Dependencies wandb tqdm pytorch = 1.7.0 numpy = 1.20.0 scipy = 1.1.0 pycolab == 1.2 Weights and Biases O
Audio-to-symbolic Arrangement via Cross-modal Music Representation Learning
Automatic Audio-to-symbolic Arrangement This is the repository of the project "Audio-to-symbolic Arrangement via Cross-modal Music Representation Lear
Implementation of CSRL from the AAAI2022 paper: Constraint Sampling Reinforcement Learning: Incorporating Expertise For Faster Learning
CSRL Implementation of CSRL from the AAAI2022 paper: Constraint Sampling Reinforcement Learning: Incorporating Expertise For Faster Learning Python: 3
The official implementation of paper "Finding the Task-Optimal Low-Bit Sub-Distribution in Deep Neural Networks" (IJCV under review).
DGMS This is the code of the paper "Finding the Task-Optimal Low-Bit Sub-Distribution in Deep Neural Networks". Installation Our code works with Pytho
Calibrated Hyperspectral Image Reconstruction via Graph-based Self-Tuning Network.
mask-uncertainty-in-HSI This repository contains the testing code and pre-trained models for the paper Calibrated Hyperspectral Image Reconstruction v
PyTorch code for 'Efficient Single Image Super-Resolution Using Dual Path Connections with Multiple Scale Learning'
Efficient Single Image Super-Resolution Using Dual Path Connections with Multiple Scale Learning This repository is for EMSRDPN introduced in the foll
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
An Intelligent Self-driving Truck System For Highway Transportation
Inceptio Intelligent Truck System An Intelligent Self-driving Truck System For Highway Transportation Note The code is still in development. OS requir