5235 Repositories
Python learning-rate Libraries
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.
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
Farlimit - FastAPI rate limit with python
FastAPIRateLimit Contributing is F&E (free&easy) Y Usage pip install farlimit N
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
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
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
Deep learning with TensorFlow and earth observation data.
Deep Learning with TensorFlow and EO Data Complete file set for Jupyter Book Autor: Development Seed Date: 04 October 2021 ISBN: (to come) Notebook tu
GANfolk: Using AI to create portraits of fictional people to sell as NFTs
GANfolk are AI-generated renderings of fictional people. Each image in the collection was created by a pair of Generative Adversarial Networks (GANs) with names and backstories also created with AI. The GANs were trained using portraits from artists like Renoir, Turner, and Modigliani in addition to open-source, modern photos.
Finding a method to objectively quantify skill expression in games, using reinforcement learning
Analyzing Skill Expression in Games This is a repo where I describe a method to measure the amount of skill expression games have. Table of Contents M
Machine learning and Deep learning models, deploy on telegram (the best social media)
Semi Intelligent BOT The project involves : Classifying fake news Classifying objects such as aeroplane, automobile, bird, cat, deer, dog, frog, horse
This repository contains the exercises and its solution contained in the book "An Introduction to Statistical Learning" in python.
An-Introduction-to-Statistical-Learning This repository contains the exercises and its solution contained in the book An Introduction to Statistical L
Notebooks for my "Deep Learning with TensorFlow 2 and Keras" course
Deep Learning with TensorFlow 2 and Keras – Notebooks This project accompanies my Deep Learning with TensorFlow 2 and Keras trainings. It contains the
🎁 3,000,000+ Unsplash images made available for research and machine learning
The Unsplash Dataset The Unsplash Dataset is made up of over 250,000+ contributing global photographers and data sourced from hundreds of millions of
Machine Learning Course with Python:
A Machine Learning Course with Python Table of Contents Download Free Deep Learning Resource Guide Slack Group Introduction Motivation Machine Learnin
Deep Learning and Reinforcement Learning Library for Scientists and Engineers 🔥
TensorLayer is a novel TensorFlow-based deep learning and reinforcement learning library designed for researchers and engineers. It provides an extens
Trax — Deep Learning with Clear Code and Speed
Trax — Deep Learning with Clear Code and Speed Trax is an end-to-end library for deep learning that focuses on clear code and speed. It is actively us
An educational resource to help anyone learn deep reinforcement learning.
Status: Maintenance (expect bug fixes and minor updates) Welcome to Spinning Up in Deep RL! This is an educational resource produced by OpenAI that ma
A collection of machine learning examples and tutorials.
machine_learning_examples A collection of machine learning examples and tutorials.
Flappy Bird hack using Deep Reinforcement Learning (Deep Q-learning).
Using Deep Q-Network to Learn How To Play Flappy Bird 7 mins version: DQN for flappy bird Overview This project follows the description of the Deep Q
deep learning for image processing including classification and object-detection etc.
深度学习在图像处理中的应用教程 前言 本教程是对本人研究生期间的研究内容进行整理总结,总结的同时也希望能够帮助更多的小伙伴。后期如果有学习到新的知识也会与大家一起分享。 本教程会以视频的方式进行分享,教学流程如下: 1)介绍网络的结构与创新点 2)使用Pytorch进行网络的搭建与训练 3)使用Te
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
Natural Language Processing Best Practices & Examples
NLP Best Practices In recent years, natural language processing (NLP) has seen quick growth in quality and usability, and this has helped to drive bus
Easy-to-use,Modular and Extendible package of deep-learning based CTR models .
DeepCTR DeepCTR is a Easy-to-use,Modular and Extendible package of deep-learning based CTR models along with lots of core components layers which can
The repository is about 100+ python programming exercise problem discussed, explained, and solved in different ways
Break The Ice With Python A journey of 100+ simple yet interesting problems which are explained, solved, discussed in different pythonic ways Introduc
Machine Learning University: Accelerated Natural Language Processing Class
Machine Learning University: Accelerated Natural Language Processing Class This repository contains slides, notebooks and datasets for the Machine Lea
This repo contains the implementation of YOLOv2 in Keras with Tensorflow backend.
Easy training on custom dataset. Various backends (MobileNet and SqueezeNet) supported. A YOLO demo to detect raccoon run entirely in brower is accessible at https://git.io/vF7vI (not on Windows).
Notes on the Deep Learning book from Ian Goodfellow, Yoshua Bengio and Aaron Courville (2016)
The Deep Learning Book - Goodfellow, I., Bengio, Y., and Courville, A. (2016) This content is part of a series following the chapter 2 on linear algeb
Code and data accompanying Natural Language Processing with PyTorch
Natural Language Processing with PyTorch Build Intelligent Language Applications Using Deep Learning By Delip Rao and Brian McMahan Welcome. This is a
Gathers machine learning and Tensorflow deep learning models for NLP problems, 1.13 Tensorflow 2.0
NLP-Models-Tensorflow, Gathers machine learning and tensorflow deep learning models for NLP problems, code simplify inside Jupyter Notebooks 100%. Tab
🙄 Difficult algorithm, Simple code.
🎉TensorFlow2.0-Examples🎉! "Talk is cheap, show me the code." ----- Linus Torvalds Created by YunYang1994 This tutorial was designed for easily divin
FMA: A Dataset For Music Analysis
FMA: A Dataset For Music Analysis Michaël Defferrard, Kirell Benzi, Pierre Vandergheynst, Xavier Bresson. International Society for Music Information
Pure python implementations of popular ML algorithms.
Minimal ML algorithms This repo includes minimal implementations of popular ML algorithms using pure python and numpy. The purpose of these notebooks
Housing Price Prediction Using Machine Learning.
HOUSING PRICE PREDICTION USING MACHINE LEARNING DESCRIPTION Housing Price Prediction Using Machine Learning is to predict the data of housings. Here I
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
A collection of data structures and algorithms I'm writing while learning
Data Structures and Algorithms: This is a collection of data structures and algorithms that I write while learning the subject Stack: stack.py A stack
Repository for the paper : Meta-FDMixup: Cross-Domain Few-Shot Learning Guided byLabeled Target Data
1 Meta-FDMIxup Repository for the paper : Meta-FDMixup: Cross-Domain Few-Shot Learning Guided byLabeled Target Data. (ACM MM 2021) paper News! the rep
Official Implementation for Fast Training of Neural Lumigraph Representations using Meta Learning.
Fast Training of Neural Lumigraph Representations using Meta Learning Project Page | Paper | Data Alexander W. Bergman, Petr Kellnhofer, Gordon Wetzst
Transfer Learning for Pose Estimation of Illustrated Characters
bizarre-pose-estimator Transfer Learning for Pose Estimation of Illustrated Characters Shuhong Chen *, Matthias Zwicker * WACV2022 [arxiv] [video] [po
Meta Learning Backpropagation And Improving It (VSML)
Meta Learning Backpropagation And Improving It (VSML) This is research code for the NeurIPS 2021 publication Kirsch & Schmidhuber 2021. Many concepts
To attract customers, the hotel chain has added to its website the ability to book a room without prepayment
To attract customers, the hotel chain has added to its website the ability to book a room without prepayment. We need to predict whether the customer is going to reject the booking or not. Since in case of refusal, the hotel incurs losses.
Deep Learning pipeline for motor-imagery classification.
BCI-ToolBox 1. Introduction BCI-ToolBox is deep learning pipeline for motor-imagery classification. This repo contains five models: ShallowConvNet, De
Using machine learning to predict undergrad college admissions.
College-Prediction Project- Overview: Many have tried, many have failed. Few trailblazers are ambitious enought to chase acceptance into the top 15 un
Neural-net-from-scratch - A simple Neural Network from scratch in Python using the Pymathrix library
A Simple Neural Network from scratch A Simple Neural Network from scratch in Pyt
Auto_code_complete is a auto word-completetion program which allows you to customize it on your needs
auto_code_complete is a auto word-completetion program which allows you to customize it on your needs. the model for this program is one of the deep-learning NLP(Natural Language Process) model structure called 'GRU(gated recurrent unit)'.
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
Implementation of deep learning models for time series in PyTorch.
List of Implementations: Currently, the reimplementation of the DeepAR paper(DeepAR: Probabilistic Forecasting with Autoregressive Recurrent Networks
Fully Convlutional Neural Networks for state-of-the-art time series classification
Deep Learning for Time Series Classification As the simplest type of time series data, univariate time series provides a reasonably good starting poin
Machine Learning for Time-Series with Python.Published by Packt
Machine-Learning-for-Time-Series-with-Python Become proficient in deriving insights from time-series data and analyzing a model’s performance Links Am
Deep Learning for Time Series Classification
Deep Learning for Time Series Classification This is the companion repository for our paper titled "Deep learning for time series classification: a re
U-Time: A Fully Convolutional Network for Time Series Segmentation
U-Time & U-Sleep Official implementation of The U-Time [1] model for general-purpose time-series segmentation. The U-Sleep [2] model for resilient hig
Tensorflow implementation of paper: Learning to Diagnose with LSTM Recurrent Neural Networks.
Multilabel time series classification with LSTM Tensorflow implementation of model discussed in the following paper: Learning to Diagnose with LSTM Re
The Wearables Development Toolkit - a development environment for activity recognition applications with sensor signals
Wearables Development Toolkit (WDK) The Wearables Development Toolkit (WDK) is a framework and set of tools to facilitate the iterative development of
DeltaPy - Tabular Data Augmentation (by @firmai)
DeltaPy — Tabular Data Augmentation & Feature Engineering Finance Quant Machine Learning ML-Quant.com - Automated Research Repository Introduction T
A Python package for time series augmentation
tsaug tsaug is a Python package for time series augmentation. It offers a set of augmentation methods for time series, as well as a simple API to conn
Deep learning PyTorch library for time series forecasting, classification, and anomaly detection
Deep learning for time series forecasting Flow forecast is an open-source deep learning for time series forecasting framework. It provides all the lat
Library for time-series-forecasting-as-a-service.
TIMEX TIMEX (referred in code as timexseries) is a framework for time-series-forecasting-as-a-service. Its main goal is to provide a simple and generi
Python implementation of the Learning Time-Series Shapelets method, that learns a shapelet-based time-series classifier with gradient descent.
shaplets Python implementation of the Learning Time-Series Shapelets method by Josif Grabocka et al., that learns a shapelet-based time-series classif
Elastic weight consolidation technique for incremental learning.
Overcoming-Catastrophic-forgetting-in-Neural-Networks Elastic weight consolidation technique for incremental learning. About Use this API if you dont
Algorithms for outlier, adversarial and drift detection
Alibi Detect is an open source Python library focused on outlier, adversarial and drift detection. The package aims to cover both online and offline d
Automated Time Series Forecasting
AutoTS AutoTS is a time series package for Python designed for rapidly deploying high-accuracy forecasts at scale. There are dozens of forecasting mod