Python Classification-models Resources

IMAX: Interactive Multi-image Analysis eXplorer This is an interactive tool for visualize and classify multiple images at a time. It written in Python

How to use TensorLayer While research in Deep Learning continues to improve the world, we use a bunch of tricks to implement algorithms with TensorLay

The lightweight PyTorch wrapper for high-performance AI research. Scale your models, not the boilerplate. Website • Key Features • How To Use • Docs •

Face Recognition: Too Bias, or Not Too Bias? Robinson, Joseph P., Gennady Livitz, Yann Henon, Can Qin, Yun Fu, and Samson Timoner. "Face recognition:

SageMaker Python SDK SageMaker Python SDK is an open source library for training and deploying machine learning models on Amazon SageMaker. With the S

BERT ***** New March 11th, 2020: Smaller BERT Models ***** This is a release of 24 smaller BERT models (English only, uncased, trained with WordPiece

zeroshot_topics Table of Contents Installation Usage License Installation zeroshot_topics is distributed on PyPI as a universal wheel and is available

EEG Classification   The task requires us to classify electroencephalography(EEG) into six categories, including human body, human face, animal body,

Biterm Topic Model Bitermplus implements Biterm topic model for short texts introduced by Xiaohui Yan, Jiafeng Guo, Yanyan Lan, and Xueqi Cheng. Actua

pyRiemann pyRiemann is a python package for covariance matrices manipulation and classification through Riemannian geometry. The primary target is cla

Text Classification The purpose of this repository is to create a neural network model of NLP with deep learning for binary classification of texts re

IntroNeuralNetworks in Python: A Template Project IntroNeuralNetworks is a project that introduces neural networks and illustrates an example of how o

AstronomicAL An interactive dashboard for visualisation, integration and classification of data using Active Learning. AstronomicAL is a human-in-the-

🤗 Hugging Face Transformer submillisecond inference 🤯 and deployment on Nvidia Triton server Yes, you can perfom inference with transformer based mo

STANFORD CARS DATASET stanford-cars "The Cars dataset contains 16,185 images of 196 classes of cars. The data is split into 8,144 training images and

Twitter COVID-19 Sentiment Analysis Members: Christopher Bach | Khalid Hamid Fallous | Jay Hirpara | Jing Tang | Graham Thomas | David Wetherhold Pro

Learning Causal Semantic Representation for Out-of-Distribution Prediction This repository is the official implementation of "Learning Causal Semantic

go-cqhttp API typing annoations, return data models and utils for nonebot

hierarchical-multi-label-text-classification-pytorch Hierarchical Multi-label Text Classification: An Attention-based Recurrent Network Approach This

Hyperlinks for pydantic models In a typical web application relationships between resources are modeled by primary and foreign keys in a database (int

ML Privacy Meter Machine learning is playing a central role in automated decision making in a wide range of organization and service providers. The da

SummaC: Summary Consistency Detection This repository contains the code for TACL2021 paper: SummaC: Re-Visiting NLI-based Models for Inconsistency Det

flower-classification-inceptionV3 Flower classification model that classifies flowers in 10 classes. Training and validation are done using a pre-anot

A multi-platform GUI for bit-based analysis, processing, and visualization

Rule-based Representation Learner This is a PyTorch implementation of Rule-based Representation Learner (RRL) as described in NeurIPS 2021 paper: Scal

Spanish Language Models 💃🏻 A repository part of the MarIA project. Corpora 📃 Corpora Number of documents Number of tokens Size (GB) BNE 201,080,084

HyperMix Code for our paper GPT3Mix and conducting classification experiments using GPT-3 prompt-based data augmentation. Getting Started Installing P

InvTorch: Memory-Efficient Invertible Functions This module extends the functionality of torch.utils.checkpoint.checkpoint to work with invertible fun

Experimental code for paper: Generative Adversarial Networks as Variational Training of Energy Based Models, under review at ICLR 2017 requirements: T

Defense-GAN: Protecting Classifiers Against Adversarial Attacks Using Generative Models Pouya Samangouei*, Maya Kabkab*, Rama Chellappa [*: authors co

AmbientGAN: Generative models from lossy measurements This repository provides code to reproduce results from the paper AmbientGAN: Generative models

Adversarial Video Generation This project implements a generative adversarial network to predict future frames of video, as detailed in "Deep Multi-Sc

A Tensorflow implementation of the Text Conditioned Auxiliary Classifier Generative Adversarial Network for Generating Images from text descriptions

Some tentative models that incorporate label propagation to graph neural networks for graph representation learning in nodes, links or graphs.

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

Ladder Variational Autoencoders (LVAE) PyTorch implementation of Ladder Variational Autoencoders (LVAE) [1]: where the variational distributions q at

tensorflow-generative-model-collections Tensorflow implementation of various GANs and VAEs. Related Repositories Pytorch version Pytorch version of th

Hummingbird Introduction Hummingbird is a library for compiling trained traditional ML models into tensor computations. Hummingbird allows users to se

LowRankModels.jl LowRankModels.jl is a Julia package for modeling and fitting generalized low rank models (GLRMs). GLRMs model a data array by a low r

pmdarima Pmdarima (originally pyramid-arima, for the anagram of 'py' + 'arima') is a statistical library designed to fill the void in Python's time se

pmdarima Pmdarima (originally pyramid-arima, for the anagram of 'py' + 'arima') is a statistical library designed to fill the void in Python's time se

health-lesion-stovol healthy and lesion models for learning based on the joint estimation of stochasticity and volatility Reference please cite this p

CSF Code of Classification Saliency-Based Rule for Visible and Infrared Image Fusion Tips: For testing: CUDA_VISIBLE_DEVICES=0 python main.py For trai

High performance distributed framework for training deep learning recommendation models based on PyTorch.

SSRL-for-image-classification Semi-supervised Representation Learning for Remote Sensing Image Classification Based on Generative Adversarial Networks

Deploy pytorch classification model using Flask and Streamlit

nbdev template Use this template to more easily create your nbdev project. If you are using an older version of this template, and want to upgrade to

vartests is a Python library to perform some statistic tests to evaluate Value at Risk (VaR) Models, such as: T-test: verify if mean of distribution i

PSLA: Improving Audio Tagging with Pretraining, Sampling, Labeling, and Aggregation Introduction Getting Started FSD50K Recipe AudioSet Recipe Label E

RATE: Overcoming Noise and Sparsity of Textual Features in Real-Time Location Estimation This is the implementation of RATE: Overcoming Noise and Spar

DeepXML Code for DeepXML: A Deep Extreme Multi-Label Learning Framework Applied to Short Text Documents Architectures and algorithms DeepXML supports

Improving Compound Activity Classification via Deep Transfer and Representation Learning This repository is the official implementation of Improving C

Scalable Intervention Target Estimation in Linear Models Implementation of the paper Scalable Intervention Target Estimation in Linear Models (NeurIPS

RobustBioNLP Improving the robustness and performance of biomedical NLP models through adversarial training In this repository you can find suppliment

DataCLUE: A Benchmark Suite for Data-centric NLP You can get the english version of README. 以数据为中心的AI测评(DataCLUE) 内容导引 章节 描述 简介 介绍以数据为中心的AI测评(DataCLUE

diffusion-channels Source code for paper "Deep Diffusion Models for Robust Channel Estimation". Generic flow: Use 'matlab/main.mat' to generate traini

Interpreting Language Models Through Knowledge Graph Extraction Idea: How do we interpret what a language model learns at various stages of training?

TaCL: Improving BERT Pre-training with Token-aware Contrastive Learning Authors: Yixuan Su, Fangyu Liu, Zaiqiao Meng, Lei Shu, Ehsan Shareghi, and Nig

AfriBERTa: Exploring the Viability of Pretrained Multilingual Language Models for Low-resourced Languages This repository contains the code for the pa

Interactive Web App with Streamlit and Scikit-learn that applies different Classification algorithms to popular datasets Datasets Used: Iris dataset,

liquid_scikit_learn Scikit learn library models to account for data and concept drift. This python library focuses on solving data drift and concept d

The code in this toolbox implements the "Spectralformer: Rethinking hyperspectral image classification with transformers". More specifically, it is detailed as follow.

time-series-classification Short and long time series classification via convolutional neural networks In this project, we present a novel framework f

NOTE: sktime-dl is currently being updated to work correctly with sktime 0.6, and wwill be fully relaunched over the summer. The plan is Refactor and

ROCKET + MINIROCKET ROCKET: Exceptionally fast and accurate time series classification using random convolutional kernels. Data Mining and Knowledge D

survivalstan: Survival Models in Stan author: Jacki Novik Overview Library of Stan Models for Survival Analysis Features: Variety of standard survival

Python Causal Impact Causal inference using Bayesian structural time-series models. This package aims at defining a python equivalent of the R CausalI

DoWhy | An end-to-end library for causal inference Amit Sharma, Emre Kiciman Introducing DoWhy and the 4 steps of causal inference | Microsoft Researc

Responsible Machine Learning With Great Power Comes Great Responsibility. Voltaire (well, maybe) How to develop machine learning models in a responsib

InterpretML - Alpha Release In the beginning machines learned in darkness, and data scientists struggled in the void to explain them. Let there be lig

AdaNet is a lightweight TensorFlow-based framework for automatically learning high-quality models with minimal expert intervention. AdaNet buil

onelearn: Online learning in Python Documentation | Reproduce experiments | onelearn stands for ONE-shot LEARNning. It is a small python package for o

Uniformer - Pytorch Implementation of Uniformer, a simple attention and 3d convolutional net that achieved SOTA in a number of video classification ta

m2cgen (Model 2 Code Generator) - is a lightweight library which provides an easy way to transpile trained statistical models into a native code

Model Serving Made Easy BentoML is a flexible, high-performance framework for serving, managing, and deploying machine learning models. Supports multi

Attention Gated Networks (Image Classification & Segmentation) Pytorch implementation of attention gates used in U-Net and VGG-16 models. The framewor

Laplacian Pyramid Reconstruction and Refinement for Semantic Segmentation This repository contains code and models for the method described in: Golnaz

PixelNet: Representation of the pixels, by the pixels, and for the pixels. We explore design principles for general pixel-level prediction problems, f

semantic-segmentation-tensorflow This is a Tensorflow implementation of semantic segmentation models on MIT ADE20K scene parsing dataset and Cityscape

Semantic Segmentation in PyTorch Semantic Segmentation in PyTorch Requirements Main Features Models Datasets Losses Learning rate schedulers Data augm

Python library with Neural Networks for Image Segmentation based on Keras and TensorFlow. The main features of this library are: High level API (just

Image Segmentation Keras : Implementation of Segnet, FCN, UNet, PSPNet and other models in Keras. Implementation of various Deep Image Segmentation mo

ZF_UNET_224 Pretrained Model Modification of convolutional neural net "UNET" for image segmentation in Keras framework Requirements Python 3.*, Keras

CNN Based Meta-Learning for Noisy Image Classification and Template Matching Introduction This master thesis used a few-shot meta learning approach to

PyTorch-LIT PyTorch-LIT is the Lite Inference Toolkit (LIT) for PyTorch which focuses on easy and fast inference of large models on end-devices. With

AlbUNet-1D-2D-Tensorflow-Keras This repository contains 1D and 2D Signal Segmentation Model Builder for AlbUNet and several of its variants developed

Python based framework for Automatic AI for Regression and Classification over numerical data. Performs model search, hyper-parameter tuning, and high-quality Jupyter Notebook code generation.

pygsflow pyGSFLOW is a python package to Create, Read, Write, Edit, and Visualize GSFLOW models API Documentation pyGSFLOW API documentation can be fo

ResNEsts and DenseNEsts: Block-based DNN Models with Improved Representation Guarantees This repository is the official implementation of the empirica

Luminous is a framework for testing the performance of Embodied AI (EAI) models in indoor tasks. Generally, we intergrete different kind of functional

Climate Modeling with Neural Diffusion Equation Introduction This is the repository of our accepted ICDM 2021 paper "Climate Modeling with Neural Diff

LSTM-Time-Series-Prediction A Simple LSTM-Based Solution for "Heartbeat Signal Classification and Prediction" in Tianchi Contest. The Link of the Cont

PyTorch 图像分类 依赖库的下载与安装 在终端中执行 pip install -r -requirements.txt 完成项目依赖库的安装 使用方式 数据集的准备 STL10 数据集 下载：STL-10 Dataset 存储位置：将下载后的数据集中 train_X.bin,train_y.b

Deep Neural Network Prediction Step 1. Genernate random parameters and Run them sequentially : $ python3 collect_data.py -gp -ep -pp -pl pooling -num

Distribution System Model Calibration Algorithms The code in this library was developed by Sandia National Laboratories under funding provided by the

IMDB film review sentiment classification based on BERT's supervised learning model. On the other hand, the model can be extended to other natural language multi-classification tasks.

Music Classification: Beyond Supervised Learning, Towards Real-world Applications

Pano3D A Holistic Benchmark and a Solid Baseline for 360o Depth Estimation Pano3D is a new benchmark for depth estimation from spherical panoramas. We

MQBench Quantization Aware Training with PyTorch I am using MQBench(Model Quantization Benchmark)(http://mqbench.tech/) to quantize the model for depl

BayeesNetworks-Image-Classification Alphabetical Letter Recognition In these demo we are using "Bayees Networks" Our database is composed by Learning