Python Classification-models Resources

OptiPLANT OptiPLANT is a cloud-based based system that empowers professional and non-professional data scientists to build high-quality predictive mod

In this project it was used some different Machine Learning models to identify the gender of a voice (Female or Male) based on some specific speech and voice attributes.

FinerFact This is the PyTorch implementation for the FinerFact model in the AAAI 2022 paper Towards Fine-Grained Reasoning for Fake News Detection (Ar

GreaseLM: Graph REASoning Enhanced Language Models This repo provides the source code & data of our paper "GreaseLM: Graph REASoning Enhanced Language

Contriever: Towards Unsupervised Dense Information Retrieval with Contrastive Learning This repository contains pre-trained models and some evaluation

TweebankNLP This repo contains the new Tweebank-NER dataset and off-the-shelf Twitter-Stanza pipeline for state-of-the-art Tweet NLP, as described in

SWAG: Supervised Weakly from hashtAGs This repository contains SWAG models from the paper Revisiting Weakly Supervised Pre-Training of Visual Percepti

On Out-of-distribution Detection with Energy-based Models This repository contains the code for the experiments conducted in the paper On Out-of-distr

PyTorch META-DATASET (Few-shot classification benchmark) This repo contains a PyTorch implementation of meta-dataset and a unified implementation of s

Mixture of Volumetric Primitives -- Training and Evaluation This repository contains code to train and render Mixture of Volumetric Primitives (MVP) m

Evidential Softmax for Sparse Multimodal Distributions in Deep Generative Models Abstract Many applications of generative models rely on the marginali

Boltzmann visualization - Visualize the Boltzmann distribution for simple quantum models of molecular motion

Vit-ImageClassification Introduction This project uses ViT to perform image clas

Labelbox Labelbox is the fastest way to annotate data to build and ship artificial intelligence applications. Use this github repository to help you s

Computer Vision Annotation Tool (CVAT) CVAT is free, online, interactive video and image annotation tool for computer vision. It is being used by our

f-BRS: Rethinking Backpropagating Refinement for Interactive Segmentation [Paper] [PyTorch] [MXNet] [Video] This repository provides code for training

BERTopic BERTopic is a topic modeling technique that leverages 🤗 transformers and c-TF-IDF to create dense clusters allowing for easily interpretable

This repo supplements our Survey on Transformers in Medical Imaging Fahad Shamshad, Salman Khan, Syed Waqas Zamir, Muhammad Haris Khan, Munawar Hayat,

COVID-ViT COVID-VIT: Classification of Covid-19 from CT chest images based on vision transformer models This code is to response to te MIA-COV19 compe

TransMIL: Transformer based Correlated Multiple Instance Learning for Whole Slide Image Classification [NeurIPS 2021] Abstract Multiple instance learn

Cascaded-FCN This repository contains the pre-trained models for a Cascaded-FCN in caffe and tensorflow that segments the liver and its lesions out of

ild-cnn This is supplementary material for the manuscript: "Lung Pattern Classification for Interstitial Lung Diseases Using a Deep Convolutional Neur

Band-Adaptive Spectral-Spatial Feature Learning Neural Network for Hyperspectral Image Classification

Raster Vision is an open source Python framework for building computer vision models on satellite, aerial, and other large imagery sets (including obl

Deep learning for Earth Observation This repository contains code, network definitions and pre-trained models for working on remote sensing images usi

self-driving-car In this repository I will share the source code of all the projects of Udacity Self-Driving Car Engineer Nanodegree. Hope this might

A collection of semantic image segmentation models implemented in TensorFlow. Contains data-loaders for the generic and medical benchmark datasets.

On Evaluation Metrics for Graph Generative Models Authors: Rylee Thompson, Boris Knyazev, Elahe Ghalebi, Jungtaek Kim, Graham Taylor This is the offic

Creating Multi Task Models With Keras About The Project! I used the keras and Tensorflow Library, To build a Deep Learning Neural Network to Creating

Diabetes Prediction Using Decision Tree Introduction Decision tree is the most powerful and popular tool for classification and prediction. A Decision

Disaster Classificiation using CNNs bunnysaini/Disaster-Classificiation Goal To prepare an image processing model to classify the type of disaster bas

ESGD-M - A stochastic non-convex second order optimizer, suitable for training deep learning models, for PyTorch

Feature engineering and machine learning: together at last! Lambdo is a workflow engine which significantly simplifies data analysis by unifying featu

**Tutorials, examples, collections, and everything else that falls into the categories: pattern classification, machine learning, and data mining.** S

Sentiment Classification using WSD, Maximum Entropy & Naive Bayes Classifiers

TResNet: High Performance GPU-Dedicated Architecture paperV2 | pretrained models Official PyTorch Implementation Tal Ridnik, Hussam Lawen, Asaf Noy, I

A research on image classification and auto insurance claim prediction, a systematic experiments on modeling techniques and approaches

You can perform Land Cover Classification on Satellite Images using Random Forest and visualize the result using Earthpy package. Make sure to install the required packages and such as

ocrd_detectron2 OCR-D wrapper for detectron2 based segmentation models Introduction Installation Usage OCR-D processor interface ocrd-detectron2-segm

Starter code: Kaggle Toxic Comment Classification Challenge More competitions 🎇 Check collection of public projects 🎁 , where you can find multiple

Language Models as Zero-Shot Planners: Extracting Actionable Knowledge for Embodied Agents [Project Page] [Paper] [Video] Wenlong Huang1, Pieter Abbee

This project has Classification and Clustering done Via kNN and K-Means respectfully. It later tests its efficiency via F1/accuracy/recall/precision for kNN and Davies-Bouldin Index for Clustering. The Data is also visually represented.

Pre-trained models based on TensorLayerX. TensorLayerX is a multi-backend AI fra

Deep-Learning-Project This Deep Learning Model Predicts that from which disease you are suffering. This Project Covers the Topics of Deep Learning Int

The aim of the mini project is predict whether or not a passenger survived based on attributes such as their age, sex, passenger class, where they embarked and more.

Binary Classification Problem with Machine Learning Solving Approach: 1) Ultimate Goal of the Assignment: This assignment is about solving a binary cl

Blackstone Blackstone is a spaCy model and library for processing long-form, unstructured legal text. Blackstone is an experimental research project f

Grover is a model for Neural Fake News -- both generation and detection. However, it probably can also be used for other generation tasks.

ECLARE ECLARE: Extreme Classification with Label Graph Correlations @InProceedings{Mittal21b, author = "Mittal, A. and Sachdeva, N. and Agrawal

GalaXC GalaXC: Graph Neural Networks with Labelwise Attention for Extreme Classification @InProceedings{Saini21, author = {Saini, D. and Jain,

Official PyTorch implementation of "VAEBM: A Symbiosis between Variational Autoencoders and Energy-based Models" (ICLR 2021 Spotlight Paper) Zhisheng

PyTorch Image Classification Following papers are implemented using PyTorch. ResNet (1512.03385) ResNet-preact (1603.05027) WRN (1605.07146) DenseNet

This Notebook is based off an open source dataset available on where I have created models to classify patients who can potentially witness heart failure on the basis of various parameters. The best model had an accuracy of 94% and a recall of 91%

T‘rex Park is a Youzan sponsored project. Offering Chinese NLP and image models pretrained from E-commerce datasets (product titles, images, comments, etc.).

TweebankNLP This repo contains the new Tweebank-NER dataset and Twitter-Stanza p

ColossalAI-Examples This repository contains examples of training models with Co

PL-LOW A high-performance deep learning model lightweight pipeline that gradually lightens deep neural networks in order to utilize high-performance d

PyTorch Implementation of "Progressive Distillation for Fast Sampling of Diffusion Models(v-diffusion)" Unofficial PyTorch Implementation of Progressi

wine-quality-predition---classification cl;asification problem using classification models in supervised learning Wine Quality Prediction Analysis - C

Mortality risk prediction for COVID-19 patients using XGBoost models Using demographic and lab test data received from the HM Hospitales in Spain, I b

Common machine learning models' hyperparameter tuning This repo is for a collection of hyper-parameter tuning for "common" machine learning models, in

Code to reproduce the results for Statistically Robust Neural Network Classification, published in UAI 2021

Official Code Release for "CLIP-Adapter: Better Vision-Language Models with Feature Adapters" Pipeline of CLIP-Adapter CLIP-Adapter is a drop-in modul

Applying BERT Fine Tuning to Sentiment Classification on Amazon Reviews Abstract Sentiment analysis has made great progress in recent years, due to th

Gender-classification This is a ML model to classify Male and Females using some physical characterstics Data. Python Libraries like Pandas,Numpy and

pytorch-caffe-models This repo contains the original weights of some Caffe models, ported to PyTorch. Currently there are: GoogLeNet (Going Deeper wit

Mixed neural likelihood estimation for models of decision-making Mixed neural likelihood estimation (MNLE) enables Bayesian parameter inference for mo

this is a simple artificial neural network model using deep learning and torch-audio to classify cats and dog sounds.

The free Zetane Viewer is a tool to help understand and accelerate discovery in machine learning and artificial neural networks. It can be used to ope

Pytorch Implementation of Augmenting Convolutional networks with attention-based aggregation This is the unofficial PyTorch Implementation of "Augment

SimTSC This is the PyTorch implementation of SDM2022 paper Towards Similarity-Aware Time-Series Classification. We propose Similarity-Aware Time-Serie

Hello, This Notebook Contains Example of Corona Virus Tweets Multi Class Classification. - Classes is: Extremely Positive, Positive, Extremely Negativ

ML_Model_implementaion Implementation of ML models like Decision tree, Naive Bayes, Logistic Regression and many other dectree_model: Implementation o

VIMuRe Latent Network Models to Account for Noisy, Multiply-Reported Social Network Data. If you use this code please cite this article (preprint). De

MlTr: Multi-label Classification with Transformer This is official implement of "MlTr: Multi-label Classification with Transformer". Abstract The task

FGVC8 Exploring Vision Transformers for Fine-grained Classification paper presented at the CVPR 2021, The Eight Workshop on Fine-Grained Visual Catego

Credit Risk Modeling in Python Introduction: If you've ever applied for a credit card or loan, you know that financial firms process your information

Brain-Tumor-Classification-with-MRI VGG16 model-based classification project about brain tumor detection. First, you can check what people are doing o

NeWT: Natural World Tasks This repository contains resources for working with the NeWT dataset. ❗ At this time the binary tasks are not publicly avail

HAKE-Action HAKE-Action (TensorFlow) is a project to open the SOTA action understanding studies based on our Human Activity Knowledge Engine. It inclu

Implementing SYNTHESIZER: Rethinking Self-Attention in Transformer Models using Pytorch Reference Paper URL Author: Yi Tay, Dara Bahri, Donald Metzler

NLP PubMed Medical Research Paper Abstract (Randomized Controlled Trial) A natural language processing model for sequential sentence classification in

Credit Risk Modeling in Python Introduction: If you've ever applied for a credit card or loan, you know that financial firms process your information

This is a Image aid classification software based on python TK library development.

Node-level Graph Regression with Deep Gaussian Process Models Prerequests our implementation is mainly based on tensorflow 1.x and gpflow 1.x: python

Meta learning algorithms to train cross-lingual NLI (multi-task) models

Credit Card Fraud Detection Came across this mocked-up dataset of customer transactions at [Capital One Recruitment Challenge](https://github.com/Capi

Homepage2Vec Language-Agnostic Website Embedding and Classification based on Curlie labels https://arxiv.org/pdf/2201.03677.pdf Homepage2Vec is a pre-

JAX Models Table of Contents About The Project Getting Started Prerequisites Installation Usage Contributing License Contact About The Project The JAX

SwinMR This is the official implementation of our proposed SwinMR: Swin Transformer for Fast MRI Please cite: @article{huang2022swin, title={Swi

Emotion-EEG Set of models for emotion estimation from EEG. Composed by the combination of two deep-learing models learning together (RNN and CNN) with

Source codes for Improved Few-Shot Visual Classification (CVPR 2020), Enhancing Few-Shot Image Classification with Unlabelled Examples (WACV 2022) and Beyond Simple Meta-Learning: Multi-Purpose Models for Multi-Domain, Active and Continual Few-Shot Learning (TPAMI 2022 - in submission)

Long text token classification using LongFormer

Pneumonia Detection from X-Rays Project Overview In this project, you will apply the skills that you have acquired in this 2D medical imaging course t

Spatial unbiased GANs — Simple TensorFlow Implementation [Paper] : Toward Spatially Unbiased Generative Models (ICCV 2021) Abstract Recent image gener

MLP-Mixer-Pytorch PyTorch implementation of MLP-Mixer: An all-MLP Architecture for Vision with the function of loading official ImageNet pre-trained p

Pixel Objectness The following repository contains pretrained model for pixel objectness. Please visit our project page for the paper and visual resul

Film review classification Решение задачи классификации отзывов на фильмы на положительные и отрицательные с помощью рекуррентных нейронных сетей 1. З

Using the provided dataset which includes various book features, in order to predict the price of books, using various proposed methods and models.

Transfer Learning for MRI Images Classification This repository introduces a short project made during my stay at Neuromatch Summer School 2021. This