5646 Repositories
Python mobile-deep-learning Libraries
MAg: a simple learning-based patient-level aggregation method for detecting microsatellite instability from whole-slide images
MAg Paper Abstract File structure Dataset prepare Data description How to use MAg? Why not try the MAg_lib! Trained models Experiment and results Some
A curated list of awesome open source libraries to deploy, monitor, version and scale your machine learning
Awesome production machine learning This repository contains a curated list of awesome open source libraries that will help you deploy, monitor, versi
A curated list of awesome Machine Learning frameworks, libraries and software.
Awesome Machine Learning A curated list of awesome machine learning frameworks, libraries and software (by language). Inspired by awesome-php. If you
A curated list of awesome Deep Learning tutorials, projects and communities.
Awesome Deep Learning Table of Contents Books Courses Videos and Lectures Papers Tutorials Researchers Websites Datasets Conferences Frameworks Tools
An awesome Data Science repository to learn and apply for real world problems.
AWESOME DATA SCIENCE An open source Data Science repository to learn and apply towards solving real world problems. This is a shortcut path to start s
📚 Papers & tech blogs by companies sharing their work on data science & machine learning in production.
applied-ml Curated papers, articles, and blogs on data science & machine learning in production. ⚙️ Figuring out how to implement your ML project? Lea
Collection of machine learning related notebooks to share.
ML_Notebooks Collection of machine learning related notebooks to share. Notebooks GAN_distributed_training.ipynb In this Notebook, TensorFlow's tutori
Contains the code of my learning of Python OOP.
OOP Python This repository contains the code of my learning of Python OOP. All the code: is following PEP 8 ✅ has proper concept illustrations and com
[AI6101] Introduction to AI & AI Ethics is a core course of MSAI, SCSE, NTU, Singapore
[AI6101] Introduction to AI & AI Ethics is a core course of MSAI, SCSE, NTU, Singapore. The repository corresponds to the AI6101 of Semester 1, AY2021-2022, starting from 08/2021. The instructors of this course are Prof. Bo An, Prof. Yu Han, and Dr. Melvin Chen.
Source code for our CVPR 2019 paper - PPGNet: Learning Point-Pair Graph for Line Segment Detection
PPGNet: Learning Point-Pair Graph for Line Segment Detection PyTorch implementation of our CVPR 2019 paper: PPGNet: Learning Point-Pair Graph for Line
[PAMI 2020] Show, Match and Segment: Joint Weakly Supervised Learning of Semantic Matching and Object Co-segmentation
Show, Match and Segment: Joint Weakly Supervised Learning of Semantic Matching and Object Co-segmentation This repository contains the source code for
Reference implementation for Structured Prediction with Deep Value Networks
Deep Value Network (DVN) This code is a python reference implementation of DVNs introduced in Deep Value Networks Learn to Evaluate and Iteratively Re
SCNet: Learning Semantic Correspondence
SCNet Code Region matching code is contributed by Kai Han ([email protected]). Dense matching code is contributed by Rafael S. Rezende (rafael.sampaio_de
Deep Watershed Transform for Instance Segmentation
Deep Watershed Transform Performs instance level segmentation detailed in the following paper: Min Bai and Raquel Urtasun, Deep Watershed Transformati
FusionNet: A deep fully residual convolutional neural network for image segmentation in connectomics
FusionNet_Pytorch FusionNet: A deep fully residual convolutional neural network for image segmentation in connectomics Requirements Pytorch 0.1.11 Pyt
TransferNet: Learning Transferrable Knowledge for Semantic Segmentation with Deep Convolutional Neural Network
TransferNet: Learning Transferrable Knowledge for Semantic Segmentation with Deep Convolutional Neural Network Created by Seunghoon Hong, Junhyuk Oh,
Astrostatistics class for the MSc degree in Astrophysics at the University of Milan-Bicocca (Italy)
Astrostatistics Davide Gerosa - [email protected] University of Milano-Bicocca, 2022. Schedule Introduction Probability and Statistics I Probabi
This project intends to use SVM supervised learning to determine whether or not an individual is diabetic given certain attributes.
Diabetes Prediction Using SVM I explore a diabetes prediction algorithm using a Diabetes dataset. Using a Support Vector Machine for my prediction alg
[WWW 2022] Zero-Shot Stance Detection via Contrastive Learning
PT-HCL for Zero-Shot Stance Detection The code of this repository is constantly being updated... Please look forward to it! Introduction This reposito
IA for recognising Traffic Signs using Keras [Tensorflow]
Traffic Signs Recognition ⚠️ 🚦 Fundamentals of Intelligent Systems Introduction 📄 Development of a neural network capable of recognizing nine differ
A machine learning project which can detect and predict the skin disease through image recognition.
ML-Project-2021 A machine learning project which can detect and predict the skin disease through image recognition. The dataset used for this is the H
ISBI 2022: Cross-level Contrastive Learning and Consistency Constraint for Semi-supervised Medical Image.
Cross-level Contrastive Learning and Consistency Constraint for Semi-supervised Medical Image Introduction This repository contains the PyTorch implem
A simple python module to generate anchor (aka default/prior) boxes for object detection tasks.
PyBx WIP A simple python module to generate anchor (aka default/prior) boxes for object detection tasks. Calculated anchor boxes are returned as ndarr
Using Global fishing watch's data to build a machine learning model that can identify illegal fishing and poaching activities through satellite and geo-location data.
Using Global fishing watch's data to build a machine learning model that can identify illegal fishing and poaching activities through satellite and geo-location data.
From Perceptron model to Deep Neural Network from scratch in Python.
Neural-Network-Basics Aim of this Repository: From Perceptron model to Deep Neural Network (from scratch) in Python. ** Currently working on a basic N
Self-supervised spatio-spectro-temporal represenation learning for EEG analysis
EEG-Oriented Self-Supervised Learning and Cluster-Aware Adaptation This repository provides a tensorflow implementation of a submitted paper: EEG-Orie
The code for our paper Semi-Supervised Learning with Multi-Head Co-Training
Semi-Supervised Learning with Multi-Head Co-Training (PyTorch) Abstract Co-training, extended from self-training, is one of the frameworks for semi-su
This repository is a basic Machine Learning train & validation Template (Using PyTorch)
pytorch_ml_template This repository is a basic Machine Learning train & validation Template (Using PyTorch) TODO Markdown 사용법 Build Docker 사용법 Anacond
Synci - Learning project to create a websocket based client server messaging application
Synci Learning project to create a websocket based client server messaging appli
Generic Foreground Segmentation in Images
Pixel Objectness The following repository contains pretrained model for pixel objectness. Please visit our project page for the paper and visual resul
Weakly Supervised Segmentation with Tensorflow. Implements instance segmentation as described in Simple Does It: Weakly Supervised Instance and Semantic Segmentation, by Khoreva et al. (CVPR 2017).
Weakly Supervised Segmentation with TensorFlow This repo contains a TensorFlow implementation of weakly supervised instance segmentation as described
Code repository for Self-supervised Structure-sensitive Learning, CVPR'17
Self-supervised Structure-sensitive Learning (SSL) Ke Gong, Xiaodan Liang, Xiaohui Shen, Liang Lin, "Look into Person: Self-supervised Structure-sensi
Deep Learning for Human Part Discovery in Images - Chainer implementation
Deep Learning for Human Part Discovery in Images - Chainer implementation NOTE: This is not official implementation. Original paper is Deep Learning f
Code of the paper "Part Detector Discovery in Deep Convolutional Neural Networks" by Marcel Simon, Erik Rodner and Joachim Denzler
Part Detector Discovery This is the code used in our paper "Part Detector Discovery in Deep Convolutional Neural Networks" by Marcel Simon, Erik Rodne
Film review classification
Film review classification Решение задачи классификации отзывов на фильмы на положительные и отрицательные с помощью рекуррентных нейронных сетей 1. З
MOOSE (Multi-organ objective segmentation) a data-centric AI solution that generates multilabel organ segmentations to facilitate systemic TB whole-person research
MOOSE (Multi-organ objective segmentation) a data-centric AI solution that generates multilabel organ segmentations to facilitate systemic TB whole-person research.The pipeline is based on nn-UNet and has the capability to segment 120 unique tissue classes from a whole-body 18F-FDG PET/CT image.
auto_code_complete is a auto word-completetion program which allows you to customize it on your need
auto_code_complete v1.3 purpose and usage auto_code_complete is a auto word-completetion program which allows you to customize it on your needs. the m
Deep Ensemble Learning with Jet-Like architecture
Ransomware analysis using DEL with jet-like architecture comprising two CNN wings, a sparse AE tail, a non-linear PCA to produce a diverse feature space, and an MLP nose
Cryptocurrency Prediction with Artificial Intelligence (Deep Learning via LSTM Neural Networks)
Cryptocurrency Prediction with Artificial Intelligence (Deep Learning via LSTM Neural Networks)- Emirhan BULUT
Stock-Prediction - prediction of stock market movements using sentiment analysis and deep learning.
Stock-Prediction- In this project, we aim to enhance the prediction of stock market movements using sentiment analysis and deep learning. We divide th
Running AlphaFold2 (from ColabFold) in Azure Machine Learning
Running AlphaFold2 (from ColabFold) in Azure Machine Learning Colby T. Ford, Ph.D. Companion repository for Medium Post: How to predict many protein s
Using the provided dataset which includes various book features, in order to predict the price of books, using various proposed methods and models.
Using the provided dataset which includes various book features, in order to predict the price of books, using various proposed methods and models.
RL Algorithms with examples in Python / Pytorch / Unity ML agents
Reinforcement Learning Project This project was created to make it easier to get started with Reinforcement Learning. It now contains: An implementati
Developing your First ML Workflow of the AWS Machine Learning Engineer Nanodegree Program
Exercises and project documentation for the 3. Developing your First ML Workflow of the AWS Machine Learning Engineer Nanodegree Program
CellRank's reproducibility repository.
CellRank's reproducibility repository We believe that reproducibility is key and have made it as simple as possible to reproduce our results. Please e
A short and easy PyTorch implementation of E(n) Equivariant Graph Neural Networks
Simple implementation of Equivariant GNN A short implementation of E(n) Equivariant Graph Neural Networks for HOMO energy prediction. Just 50 lines of
Data-Uncertainty Guided Multi-Phase Learning for Semi-supervised Object Detection
An official implementation of paper Data-Uncertainty Guided Multi-Phase Learning for Semi-supervised Object Detection
Fake News Detection Using Machine Learning Methods
Fake-News-Detection-Using-Machine-Learning-Methods Fake news is always a real and dangerous issue. However, with the presence and abundance of various
The code succinctly shows how our ensemble learning based on deep learning CNN is used for LAM-avulsion-diagnosis.
deep-learning-LAM-avulsion-diagnosis The code succinctly shows how our ensemble learning based on deep learning CNN is used for LAM-avulsion-diagnosis
This repository introduces a short project about Transfer Learning for Classification of MRI Images.
Transfer Learning for MRI Images Classification This repository introduces a short project made during my stay at Neuromatch Summer School 2021. This
Cl datasets - PyTorch image dataloaders and utility functions to load datasets for supervised continual learning
Continual learning datasets Introduction This repository contains PyTorch image
Semi-Supervised Semantic Segmentation with Pixel-Level Contrastive Learning from a Class-wise Memory Bank
This repository provides the official code for replicating experiments from the paper: Semi-Supervised Semantic Segmentation with Pixel-Level Contrast
PyTorch code for JEREX: Joint Entity-Level Relation Extractor
JEREX: "Joint Entity-Level Relation Extractor" PyTorch code for JEREX: "Joint Entity-Level Relation Extractor". For a description of the model and exp
Training a Resilient Q-Network against Observational Interference, Causal Inference Q-Networks
Obs-Causal-Q-Network AAAI 2022 - Training a Resilient Q-Network against Observational Interference Preprint | Slides | Colab Demo | Environment Setup
We present a regularized self-labeling approach to improve the generalization and robustness properties of fine-tuning.
Overview This repository provides the implementation for the paper "Improved Regularization and Robustness for Fine-tuning in Neural Networks", which
Lbl2Vec learns jointly embedded label, document and word vectors to retrieve documents with predefined topics from an unlabeled document corpus.
Lbl2Vec Lbl2Vec is an algorithm for unsupervised document classification and unsupervised document retrieval. It automatically generates jointly embed
This repository collects 100 papers related to negative sampling methods.
Negative-Sampling-Paper This repository collects 100 papers related to negative sampling methods, covering multiple research fields such as Recommenda
Intel® Neural Compressor is an open-source Python library running on Intel CPUs and GPUs
Intel® Neural Compressor targeting to provide unified APIs for network compression technologies, such as low precision quantization, sparsity, pruning, knowledge distillation, across different deep learning frameworks to pursue optimal inference performance.
Deep motion generator collections
GenMotion GenMotion (/gen’motion/) is a Python library for making skeletal animations. It enables easy dataset loading and experiment sharing for synt
Make your master artistic punk avatar through machine learning world famous paintings.
Master-art-punk Make your master artistic punk avatar through machine learning world famous paintings. 通过机器学习世界名画制作属于你的大师级艺术朋克头像 Nowadays, NFT is beco
VL-LTR: Learning Class-wise Visual-Linguistic Representation for Long-Tailed Visual Recognition
VL-LTR: Learning Class-wise Visual-Linguistic Representation for Long-Tailed Visual Recognition Usage First, install PyTorch 1.7.1+, torchvision 0.8.2
Generative Autoregressive, Normalized Flows, VAEs, Score-based models (GANVAS)
GANVAS-models This is an implementation of various generative models. It contains implementations of the following: Autoregressive Models: PixelCNN, G
Sentiment-Analysis and EDA on the IMDB Movie Review Dataset
Sentiment-Analysis and EDA on the IMDB Movie Review Dataset The main part of the work focuses on the exploration and study of different approaches whi
This repository provides the official implementation of 'Learning to ignore: rethinking attention in CNNs' accepted in BMVC 2021.
inverse_attention This repository provides the official implementation of 'Learning to ignore: rethinking attention in CNNs' accepted in BMVC 2021. Le
A curated list of awesome Amazon Web Services (AWS) libraries, open source repos, guides, blogs, and other resources.
A curated list of awesome Amazon Web Services (AWS) libraries, open source repos, guides, blogs, and other resources. Featuring the Fiery Meter of AWSome.
Mapping a variable-length sentence to a fixed-length vector using BERT model
Are you looking for X-as-service? Try the Cloud-Native Neural Search Framework for Any Kind of Data bert-as-service Using BERT model as a sentence enc
Keras implementations of Generative Adversarial Networks.
This repository has gone stale as I unfortunately do not have the time to maintain it anymore. If you would like to continue the development of it as
Keras code and weights files for popular deep learning models.
Trained image classification models for Keras THIS REPOSITORY IS DEPRECATED. USE THE MODULE keras.applications INSTEAD. Pull requests will not be revi
AI and Machine Learning with Kubeflow, Amazon EKS, and SageMaker
Data Science on AWS - O'Reilly Book Get the book on Amazon.com Book Outline Quick Start Workshop (4-hours) In this quick start hands-on workshop, you
YoloV3 Implemented in Tensorflow 2.0
YoloV3 Implemented in TensorFlow 2.0 This repo provides a clean implementation of YoloV3 in TensorFlow 2.0 using all the best practices. Key Features
This is code of book "Learn Deep Learning with PyTorch"
深度学习入门之PyTorch Learn Deep Learning with PyTorch 非常感谢您能够购买此书,这个github repository包含有深度学习入门之PyTorch的实例代码。由于本人水平有限,在写此书的时候参考了一些网上的资料,在这里对他们表示敬意。由于深度学习的技术在
Python Machine Learning Jupyter Notebooks (ML website)
Python Machine Learning Jupyter Notebooks (ML website) Dr. Tirthajyoti Sarkar, Fremont, California (Please feel free to connect on LinkedIn here) Also
A set of Deep Reinforcement Learning Agents implemented in Tensorflow.
Deep Reinforcement Learning Agents This repository contains a collection of reinforcement learning algorithms written in Tensorflow. The ipython noteb
Jupyter notebooks for using & learning Keras
deep-learning-with-keras-notebooks 這個github的repository主要是個人在學習Keras的一些記錄及練習。希望在學習過程中發現到一些好的資訊與範例也可以對想要學習使用 Keras來解決問題的同好,或是對深度學習有興趣的在學學生可以有一些方便理解與上手範例
Scenarios, tutorials and demos for Autonomous Driving
The Autonomous Driving Cookbook (Preview) NOTE: This project is developed and being maintained by Project Road Runner at Microsoft Garage. This is cur
Practical Machine Learning with Python
Master the essential skills needed to recognize and solve complex real-world problems with Machine Learning and Deep Learning by leveraging the highly popular Python Machine Learning Eco-system.
Chess reinforcement learning by AlphaGo Zero methods.
About Chess reinforcement learning by AlphaGo Zero methods. This project is based on these main resources: DeepMind's Oct 19th publication: Mastering
Semi-Automated Data Processing
Perform semi automated exploratory data analysis, feature engineering and feature selection on provided dataset by visualizing every possibilities on each step and assisting the user to make a meaningful decision to achieve a low-bias and low-variance model.
To design and implement the Identification of Iris Flower species using machine learning using Python and the tool Scikit-Learn.
To design and implement the Identification of Iris Flower species using machine learning using Python and the tool Scikit-Learn.
I-Spy is a discord and twitter bot 🤖 that keeps a check on usage foul language, hate-speech and NSFW contents
I-Spy is a discord and twitter bot 🤖 that keeps a check on usage foul language, hate-speech and NSFW contents. It is the one stop solution to monitor your discord servers and twitter handles against community demons by offering content moderation.
Using knowledge-informed machine learning on the PRONOSTIA (FEMTO) and IMS bearing data sets. Predict remaining-useful-life (RUL).
Knowledge Informed Machine Learning using a Weibull-based Loss Function Exploring the concept of knowledge-informed machine learning with the use of a
Multi-Stage Episodic Control for Strategic Exploration in Text Games
XTX: eXploit - Then - eXplore Requirements First clone this repo using git clone https://github.com/princeton-nlp/XTX.git Please create two conda envi
Pytorch implementation of local motion and contrast prior driven deep network (MoCoPnet)
MoCoPnet: Exploring Local Motion and Contrast Priors for Infrared Small Target Super-Resolution Pytorch implementation of local motion and contrast pr
Soft actor-critic is a deep reinforcement learning framework for training maximum entropy policies in continuous domains.
This repository is no longer maintained. Please use our new Softlearning package instead. Soft Actor-Critic Soft actor-critic is a deep reinforcement
Towards Understanding Quality Challenges of the Federated Learning: A First Look from the Lens of Robustness
FL Analysis This repository contains the code and results for the paper "Towards Understanding Quality Challenges of the Federated Learning: A First L
Tackling the Class Imbalance Problem of Deep Learning Based Head and Neck Organ Segmentation
Info This is the code repository of the work Tackling the Class Imbalance Problem of Deep Learning Based Head and Neck Organ Segmentation from Elias T
An onlinel learning to rank python codebase.
OLTR Online learning to rank python codebase. The code related to Pairwise Differentiable Gradient Descent (ranker/PDGDLinearRanker.py) is copied from
Neural network pruning for finding a sparse computational model for controlling a biological motor task.
MothPruning Scientific Overview Originally inspired by biological nervous systems, deep neural networks (DNNs) are powerful computational tools for mo
Alignment Attention Fusion framework for Few-Shot Object Detection
AAF framework Framework generalities This repository contains the code of the AAF framework proposed in this paper. The main idea behind this work is
Deep deconfounded recommender (Deep-Deconf) for paper "Deep causal reasoning for recommendations"
Deep Causal Reasoning for Recommender Systems The codes are associated with the following paper: Deep Causal Reasoning for Recommendations, Yaochen Zh
The dynamics of representation learning in shallow, non-linear autoencoders
The dynamics of representation learning in shallow, non-linear autoencoders The package is written in python and uses the pytorch implementation to ML
A Light in the Dark: Deep Learning Practices for Industrial Computer Vision
A Light in the Dark: Deep Learning Practices for Industrial Computer Vision This is the repository for our Paper/Contribution to the WI2022 in Nürnber
Repository for the AugmentedPCA Python package.
Overview This Python package provides implementations of Augmented Principal Component Analysis (AugmentedPCA) - a family of linear factor models that
Pytorch implementation of NEGEV method. Paper: "Negative Evidence Matters in Interpretable Histology Image Classification".
Pytorch 1.10.0 code for: Negative Evidence Matters in Interpretable Histology Image Classification (https://arxiv. org/abs/xxxx.xxxxx) Citation: @arti
A Review of Deep Learning Techniques for Markerless Human Motion on Synthetic Datasets
HOW TO USE THIS PROJECT A Review of Deep Learning Techniques for Markerless Human Motion on Synthetic Datasets Based on DeepLabCut toolbox, we run wit
A Novel Incremental Learning Driven Instance Segmentation Framework to Recognize Highly Cluttered Instances of the Contraband Items
A Novel Incremental Learning Driven Instance Segmentation Framework to Recognize Highly Cluttered Instances of the Contraband Items This repository co
This code is the implementation of the paper "Coherence-Based Distributed Document Representation Learning for Scientific Documents".
Introduction This code is the implementation of the paper "Coherence-Based Distributed Document Representation Learning for Scientific Documents". If
FEMDA: Robust classification with Flexible Discriminant Analysis in heterogeneous data
FEMDA: Robust classification with Flexible Discriminant Analysis in heterogeneous data. Flexible EM-Inspired Discriminant Analysis is a robust supervised classification algorithm that performs well in noisy and contaminated datasets.
Machine Learning Model deployment for Container (TensorFlow Serving)
try_tf_serving ├───dataset │ ├───testing │ │ ├───paper │ │ ├───rock │ │ └───scissors │ └───training │ ├───paper │ ├───rock