Python Learning-models-and-generalization Resources

Kata: Clean Machine Learning From Dirty Code First, open the Kata in Google Colab (or else download it) You can clone this project and launch jupyter-

metrics-advisor Analyze reshaped metrics from TiDB cluster Prometheus and give some advice about anomalies and correlation. Team freedeaths mashenjun

Ukiyo - a simple, minimalist and efficient discord vanity URL sniper. Ukiyo is easy to use, has a very visually pleasing interface, and has great spee

SpecAugment An implementation of SpecAugment for Pytorch How to use Install pytorch, version=1.9.0 (new feature (torch.Tensor.take_along_dim) is used

fake-news-detector-1.0 Lists, lists and more lists... Spam filter list, quality keyword list, stoplist list, top-domains urls list, news agencies webs

snowfall helpful image handling utils - abstracts various file and opencv and pil features into result oriented functions usage examples: from image_h

About The Project Panorama composition using SIFT Features and a custom implementaion of RANSAC algorithm (Random Sample Consensus). Author: Andreas P

Random Word Generator Generates meaningful words from dictionary with given no. of letters and words. This might be useful for generating short links

Project Title Wakatime Response In javascript and python Description just for refrence Getting Started Dependencies For Python: requests json For Java

⭐️ String Session Generator ⭐️ Genrate String Session Using this bot. Made by TeamUltronX 🔥 String Session Demo Bot: Environment Variables Mandatory

Instagram_scrapper This project allow you to scrape the list of followers, following or both from a public Instagram account, and create a csv or exce

Puesta en Producción de un modelo de aprendizaje automático con Flask y Heroku L

Covid-19-Trends Introduction The COVID-19 pandemic has caused severe financial s

Chronocalc I wrote this script after I was busy updating my article on chronoloc

42 Event Notifier 42서울 Agenda에 새로운 이벤트가 등록되면 알려드립니다! 현재는 Github Issue로 등록되므로 상단

Minimal code and simple experiments to play with Denoising Diffusion Probabilist

A Survey on Deep Learning Technique for Video Segmentation A Survey on Deep Learning Technique for Video Segmentation Wenguan Wang, Tianfei Zhou, Fati

Easily train or fine-tune SOTA computer vision models from one training repository. SuperGradients Introduction Welcome to SuperGradients, a free open

IMBENS: Class-imbalanced Ensemble Learning in Python Language: English | Chinese/中文 Links: Documentation | Gallery | PyPI | Changelog | Source | Downl

Streamlit Translator Streamlit Translator is a simple translator app to detect and translate between languages. Streamlit Translator gets text and lan

AI-generated-characters for Learning and Wellbeing Click here for the full project page. This repository contains the source code for the paper AI-gen

Aesara is a Python library that allows one to define, optimize, and efficiently evaluate mathematical expressions involving multi-dimensional arrays.

Lightning-Hydra-Template A clean and scalable template to kickstart your deep learning project 🚀 ⚡ 🔥 Click on Use this template to initialize new re

Torchuq [logo here] TorchUQ is an extensive library for uncertainty quantification (UQ) based on pytorch. TorchUQ currently supports 10 representation

Data driven GPVAD Repository for the work in TASLP 2021 Voice activity detection in the wild: A data-driven approach using teacher-student training. S

[ICCV 2021] GyroFlow: Gyroscope-Guided Unsupervised Optical Flow Learning This is the official implementation of our ICCV2021 paper GyroFlow. Our pres

Uncertainty-Based Offline Reinforcement Learning with Diversified Q-Ensemble This is the code for reproducing the results of the paper Uncertainty-Bas

Neural Machine Translation communication system The model is basically direct to convert one source language to another targeted language using encode

WA Covid Mailer Sends alerts from Healthy WA's Covid19 Exposure Locations via email and slack. Setup Edit the configuration items in wacovidmailer.py

bootleg-productions consider this account to be a journal for me to record my progress throughout my python journey feel free to copy codes from this

Bulk2Space Spatially resolved single-cell deconvolution of bulk transcriptomes using Bulk2Space Bulk2Space is a spatial deconvolution method based on

Pytorch implementation of paper Semi-supervised Knowledge Transfer for Deep Learning from Private Training Data

Mean teachers are better role models Paper ---- NIPS 2017 poster ---- NIPS 2017 spotlight slides ---- Blog post By Antti Tarvainen, Harri Valpola (The

This repository contains source code for the experiments in a paper titled Semi-Supervised Learning with Ladder Networks by A Rasmus, H Valpola, M Hon

Training Script for Reuse-VOS This code implementation of CVPR 2021 paper : Learning Dynamic Network Using a Reuse Gate Function in Semi-supervised Vi

Code used for the results in the paper "ClassMix: Segmentation-Based Data Augmentation for Semi-Supervised Learning" Getting started Prerequisites CUD

PseudoSeg: Designing Pseudo Labels for Semantic Segmentation PseudoSeg is a simple consistency training framework for semi-supervised image semantic s

PixelSSL is a PyTorch-based semi-supervised learning (SSL) codebase for pixel-wise (Pixel) vision tasks. The purpose of this project is to promote the

Learning Saliency Propagation for Semi-supervised Instance Segmentation PyTorch Implementation This repository contains: the PyTorch implementation of

Semi-Supervised Semantic Segmentation with Cross-Consistency Training (CCT) Paper, Project Page This repo contains the official implementation of CVPR

Semi-supevised Semantic Segmentation with High- and Low-level Consistency This Pytorch repository contains the code for our work Semi-supervised Seman

USSS_ICCV19 Code for Universal Semi Supervised Semantic Segmentation accepted to ICCV 2019. Full Paper available at https://arxiv.org/abs/1811.10323.

Weakly Supervised Learning of Instance Segmentation with Inter-pixel Relations The code of: Weakly Supervised Learning of Instance Segmentation with I

Adversarial Learning for Semi-supervised Semantic Segmentation This repo is the pytorch implementation of the following paper: Adversarial Learning fo

Weakly- and Semi-Supervised Panoptic Segmentation by Qizhu Li*, Anurag Arnab*, Philip H.S. Torr This repository demonstrates the weakly supervised gro

Weakly Supervised Segmentation by Tensorflow. Implements semantic segmentation in Simple Does It: Weakly Supervised Instance and Semantic Segmentation, by Khoreva et al. (CVPR 2017).

Source code for STAC: A Simple Semi-Supervised Learning Framework for Object Detection STAC is a simple yet effective SSL framework for visual object

Wetectron Wetectron is a software system that implements state-of-the-art weakly-supervised object detection algorithms. Project CVPR'20, ECCV'20 | Pa

CSD: Consistency-based Semi-supervised learning for object Detection (NeurIPS 2019) By Jisoo Jeong, Seungeui Lee, Jee-soo Kim, Nojun Kwak Installation

COResets and Data Subset selection Reduce end to end training time from days to hours (or hours to minutes), and energy requirements/costs by an order

Neural View Synthesis and Matching for Semi-Supervised Few-Shot Learning of 3D Pose Release Notes The official PyTorch implementation of Neural View S

More Photos are All You Need: Semi-Supervised Learning for Fine-Grained Sketch Based Image Retrieval, CVPR 2021. Ayan Kumar Bhunia, Pinaki nath Chowdh

DeepDeform (CVPR'2020) DeepDeform is an RGB-D video dataset containing over 390,000 RGB-D frames in 400 videos, with 5,533 optical and scene flow imag

Semi-supervised Learning for Few-shot Image-to-Image Translation [paper] Abstract: In the last few years, unpaired image-to-image translation has witn

Deep SAD: A Method for Deep Semi-Supervised Anomaly Detection This repository provides a PyTorch implementation of the Deep SAD method presented in ou

Learning to Self-Train for Semi-Supervised Few-Shot Classification This repository contains the TensorFlow implementation for NeurIPS 2019 Paper "Lear

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

MixText This repo contains codes for the following paper: Jiaao Chen, Zichao Yang, Diyi Yang: MixText: Linguistically-Informed Interpolation of Hidden

High resolution disentanglement datasets This repository contains the Falcor3D and Isaac3D datasets, which present a state-of-the-art challenge for co

MarginGAN This repository is the implementation of the paper "MarginGAN: Adversarial Training in Semi-Supervised Learning". 1."preliminary" is the imp

Semi-supervised Adversarial Learning to Generate Photorealistic Face Images of New Identities from 3D Morphable Model Baris Gecer 1, Binod Bhattarai 1

Good Semi-Supervised Learning that Requires a Bad GAN This is the code we used in our paper Good Semi-supervised Learning that Requires a Bad GAN Ziha

Strongly local p-norm-cut algorithms for semi-supervised learning and local graph clustering

Confidence-based Graph Convolutional Networks for Semi-Supervised Learning Source code for AISTATS 2019 paper: Confidence-based Graph Convolutional Ne

Generalized Matrix Means for Semi-Supervised Learning with Multilayer Graphs MATLAB implementation of the paper: P. Mercado, F. Tudisco, and M. Hein,

Neural Structured Learning in TensorFlow Neural Structured Learning (NSL) is a new learning paradigm to train neural networks by leveraging structured

Graph-based joint model with Nonignorable Missingness (GNM) This is a Keras implementation of the GNM model in paper ’Graph-Based Semi-Supervised Lear

G3NN This repo provides a pytorch implementation for the 4 instantiations of the flexible generative framework as described in the following paper: A

few-shot-ssl-public Code for paper Meta-Learning for Semi-Supervised Few-Shot Classification. [arxiv] Dependencies cv2 numpy pandas python 2.7 / 3.5+

Semi-supervised Deep Kernel Learning This is the code that accompanies the paper Semi-supervised Deep Kernel Learning: Regression with Unlabeled Data

FAIR Self-Supervision Benchmark is deprecated. Please see VISSL, a ground-up rewrite of benchmark in PyTorch. FAIR Self-Supervision Benchmark This cod

Joint Unsupervised Learning (JULE) of Deep Representations and Image Clusters. Overview This project is a Torch implementation for our CVPR 2016 paper

Graph Contrastive Learning with Augmentations PyTorch implementation for Graph Contrastive Learning with Augmentations [poster] [appendix] Yuning You*

CCGL: Contrastive Cascade Graph Learning This repo provides a reference implementation of Contrastive Cascade Graph Learning (CCGL) framework as descr

cleaning-utils [] [] [] cleaning-utils is a collection of small Python functions

Created in about 4.5 hours discord-account-generator Creates accounts and verifi

Img-process-manual - Opencv Library basic graphic processing algorithm coding reproduction based on Numpy and Matplotlib library

PEGUARD PEGUARD is a file crypter and packing utility. This project was original

This is a scalable system that reads messages from public Telegram channels using Telethon and stores the data in a PostgreSQL database. Its original intention is to monitor cryptocurrency related channels, but it can be configured to read any Telegram data that is accessible through the API.

opt-einsum-torch There have been many implementations of Einstein's summation. numpy's numpy.einsum is the least efficient one as it only runs in sing

Scrape-Product-Aliexpress A tool can scrape product in aliexpress: Title, Price, and URL Product. Usage: 1. Install Python 3.8 3.9 padahal halaman ins

Aerospace Utilities About Module that contains commonly-used aerospace utilities for problem solving. Flight Condition: input altitude to compute comm

Works very well and you can ask for the type of image you want the scrapper to collect. Also follows a specific urls path depending on keyword selection.

Approximate Nearest Neighbor Negative Contrastive Learning for Dense Text Retrieval This repo provides personal implementation of paper Approximate Ne

Proper CLI Proper CLI is a Python package for creating beautiful, composable, and ridiculously good looking command-line-user-interfaces without havin

Visualize, analyze, and explore NLP language models. Ecco creates interactive visualizations directly in Jupyter notebooks explaining the behavior of Transformer-based language models (like GPT2, BERT, RoBERTA, T5, and T0).

Beibo is a Python library that uses several AI prediction models to predict stocks returns over a defined period of time.

Change Detection Laboratory Developing and benchmarking deep learning-based remo

GitHub English Top Charts 「Help you discover excellent English projects and get

CountDown and Shoot Fireworks About App This is an small application make you re

outputformat Python library to decorate and beautify your standard output 💖 Ins

A simplistic and efficient pure-python neural network library from Phys Whiz with CPU and GPU support.

Zero-shot-dual-iter-LLE The code of Zero-shot learning for low-light image enhancement based on dual iteration. You can get the real night image tests

This is a realtime voice translator program which gets input from user at any language and converts it to the desired language that the user asks ...

Chatto A unified API wrapper for YouTube and Twitch chat bots. Contributing Chatto is open to contributions. To find out where to get started, have a

OpenSelfSup News Downstream tasks now support more methods(Mask RCNN-FPN, RetinaNet, Keypoints RCNN) and more datasets(Cityscapes). 'GaussianBlur' is

Nestalarm Monitor an EnvisaLink alarm module running Honeywell firmware, and set a Nest device to Home/Away depending on whether the alarm is Disarmed

GCC: Graph Contrastive Coding for Graph Neural Network Pre-Training Original implementation for paper GCC: Graph Contrastive Coding for Graph Neural N

GRACE The official PyTorch implementation of deep GRAph Contrastive rEpresentation learning (GRACE). For a thorough resource collection of self-superv

GMI (Graphical Mutual Information) Graph Representation Learning via Graphical Mutual Information Maximization (Peng Z, Huang W, Luo M, et al., WWW 20