Python MIT-Machine-Learning-with-Python Resources

Python Code Obfuscator A script that converts code into full on random numerical expressions. Simple Scripts: Python Mode... Input: Function that deco

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

tsuserverMoS A Python-based server for Attorney Online, forked from RealKaiser/tsuserverCC Requires Python 3.7+ and PyYAML. Changes/additions from tsu

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

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

ValveVMF ValveVMF is a Python library for parsing .vmf files for the Source Engi

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

This is a Algo/script trading for Deribit. You need an account with deribit, to

pyfetch Simple Fetch written in Python Screenshots Install Clone this repository

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

Request Tracker Bot This is a Request Tracker Bot repo, It is for those who uplo

simplebot_tg Telegram/DeltaChat Bridge, is a plugin for https://github.com/simpl

thanks to aphitorite for the beautiful logo! opal opal is a WIP transcompiled pr

image retrieval This is a python code to retrieve an image from the internet, a

Python implementation of Aho-Corasick algorithm for string searching

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.

OpenLigaDB This is a small package to interact with the OpenLigaDB API. Installation Run the following to install: pip install openligadb Usage from o

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

Must-typing Force you (or your user) annotate function type hints. Notice: It's more like a joke, use it carefully. If you call must_typing in your mo

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

YaourtBot A discord simple bot by Lopinosaurus Before using this code : ・Move env file to .env ・Change the channel ID on line 38 of bot.py to your #pi

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

disposable-email-validator installation pip install disposable-email-validator

Python Flutterwave Description Python Wrapper for interacting with the Flutterwa

lang lang is a simple stack based programming language written in Python. It can

excel-cell-checker Description This tool checks a given .xlsx file has the struc

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.

Pylowdb Simple to use local JSON database 🦉 # This is pure python, not specific to pylowdb ;) db.data['posts'] = ({ 'id': 1, 'title': 'pylowdb is awe

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

RaspberryPi Spotify OLED Display This application will display currently played track on SSD1306 OLED display connected to RaspberryPi. Displayed stuf

Zoom Automation A python script that automatically joins a zoom meeting based on your timetable. What does it do? It performs the following processes:

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

inverted-pendulum-fuzzy-control- inverted pendulum fuzzy control python code (python 2.7.18) We have 3 general functions for 3 main steps: fuzzificati

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

SelfGNN A PyTorch implementation of "SelfGNN: Self-supervised Graph Neural Networks without explicit negative sampling" paper, which will appear in Th

Contrastive Learning of Structured World Models This repository contains the official PyTorch implementation of: Contrastive Learning of Structured Wo

DGI Deep Graph Infomax (Veličković et al., ICLR 2019): https://arxiv.org/abs/1809.10341 Overview Here we provide an implementation of Deep Graph Infom

Unsupervised Attributed Multiplex Network Embedding (DMGI) Overview Nodes in a multiplex network are connected by multiple types of relations. However

Contrastive Multi-View Representation Learning on Graphs This work introduces a self-supervised approach based on contrastive multi-view learning to l

Subg-Con Sub-graph Contrast for Scalable Self-Supervised Graph Representation Learning (Jiao et al., ICDM 2020): https://arxiv.org/abs/2009.10273 Over

Graph-InfoClust-GIC [PAKDD 2021] PAKDD'21 version Graph InfoClust: Maximizing Coarse-Grain Mutual Information in Graphs Preprint version Graph InfoClu

Introduction QRec is a Python framework for recommender systems (Supported by Python 3.7.4 and Tensorflow 1.14+) in which a number of influential and

ncnn ncnn is a high-performance neural network inference computing framework optimized for mobile platforms. ncnn is deeply considerate about deployme

Deep Hedging Demo Pricing Derivatives using Machine Learning 1) Jupyter version: Run ./colab/deep_hedging_colab.ipynb on Colab. 2) Gui version: Run py

CATs: Cost Aggregation Transformers for Visual Correspondence NeurIPS'21 For more information, check out the paper on [arXiv]. Training with different

Awesome Model-Based Reinforcement Learning This is a collection of research papers for model-based reinforcement learning (mbrl). And the repository w

OCRmyPDF adds an OCR text layer to scanned PDF files, allowing them to be searched or copy-pasted. ocrmypdf

ElegantRL “小雅”: Scalable and Elastic Deep Reinforcement Learning ElegantRL is developed for researchers and practitioners with the following advantage

algofi-py-sdk Algofi Python SDK Documentation https://algofi-py-sdk.readthedocs.

outputformater Python library to decorate and beautify your standard output 💖 I

PyStark A star ⭐ from you means a lot An incomplete add-on extension to Pyrogram

BugbountyBot Discord Bot for Bug Bounty Web The purpose of this bot is to automa

Need: Image Search The problem is that a user needs to search for a specific ima

WoRkS continued English 中文 Français Probability Density Estimation-Non-Parametric Methods(概率密度估计-非参数方法) 1. Kernel / k-Nearest Neighborhood Density Est