Python Neural-machine-translation Resources

PGExplainer This is a Tensorflow implementation of the paper: Parameterized Explainer for Graph Neural Network https://arxiv.org/abs/2011.04573 NeurIP

Using python and scikit-learn to make stock predictions

Automated machine learning: Review of the state-of-the-art and opportunities for healthcare

GLAT Implementation for the ACL2021 paper "Glancing Transformer for Non-Autoregressive Neural Machine Translation" Requirements Python = 3.7 Pytorch

​ DS2.ai is an integrated AI operation solution that supports all stages from custom AI development to deployment. It is an AI-specialized platform service that collects data, builds a training dataset through data labeling, and enables automatic development of artificial intelligence and easy deployment and operation.

UrduPython Write simple Python in Urdu. How to Use Write Urdu code in سامپل۔پے The mappings are as following: "۔": ".", "،":

Lags valorant servers by rapidly picking up and throwing shorties.

code for "AttentiveNAS Improving Neural Architecture Search via Attentive Sampling"

A collection of research papers and software related to explainability in graph machine learning.

A collection of Deep Learning images and visualizations. The project has been developed by the AI Summer team and currently contains almost 100 images.

S2-BNN (Self-supervised Binary Neural Networks Using Distillation Loss) This is the official pytorch implementation of our paper: "S2-BNN: Bridging th

Visual-Reasoning-eXplanation [CVPR 2021 A Peek Into the Reasoning of Neural Networks: Interpreting with Structural Visual Concepts] Project Page | Vid

A collection of Deep Learning images and visualizations. The project has been developed by the AI Summer team and currently contains almost 100 images.

NCRF Prerequisites Data Whole slide images Annotations Patch images Model Training Testing Tissue mask Probability map Tumor localization FROC evaluat

EfficientNet A PyTorch implementation of EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks. [arxiv] [Official TF Repo] Implemen

EigenDamage: Structured Pruning in the Kronecker-Factored Eigenbasis This repo contains the official implementations of EigenDamage: Structured Prunin

Deep Neural Networks Improve Radiologists' Performance in Breast Cancer Screening Introduction This is an implementation of the model used for breast

PyKEEN PyKEEN (Python KnowlEdge EmbeddiNgs) is a Python package designed to train and evaluate knowledge graph embedding models (incorporating multi-m

This is a curated list of tutorials, projects, libraries, videos, papers, books and anything related to the incredible PyTorch. Feel free to make a pu

Generative Models Collection of generative models, e.g. GAN, VAE in Pytorch and Tensorflow. Also present here are RBM and Helmholtz Machine. Note: Gen

Draw like Bob Ross using the power of Neural Networks! (+ Pytorch) Learning Process Visualization Getting started Install dependecies Requires python3

Deep Learning Winter School, November 2107. Tel Aviv Deep Learning Bootcamp : http://deep-ml.com. About Tel-Aviv Deep Learning Bootcamp is an intensiv

Amazon Forest Computer Vision Satellite Image tagging code using PyTorch / Keras Here is a sample of images we had to work with Source: https://www.ka

Torchreid Torchreid is a library for deep-learning person re-identification, written in PyTorch. It features: multi-GPU training support both image- a

Hasktorch Hasktorch is a library for tensors and neural networks in Haskell. It is an independent open source community project which leverages the co

Master Release Pytorch - Py + Nim A Nim frontend for pytorch, aiming to be mostly auto-generated and internally using ATen. Because Nim compiles to C+

UNet for segmenting salt deposits from seismic images with PyTorch. General We, tugstugi and xuyuan, have participated in the Kaggle competition TGS S

The Medical Detection Toolkit contains 2D + 3D implementations of prevalent object detectors such as Mask R-CNN, Retina Net, Retina U-Net, as well as a training and inference framework focused on dealing with medical images.

ocaml-torch provides some ocaml bindings for the PyTorch tensor library. This brings to OCaml NumPy-like tensor computations with GPU acceleration and tape-based automatic differentiation.

tch-rs Rust bindings for the C++ api of PyTorch. The goal of the tch crate is to provide some thin wrappers around the C++ PyTorch api (a.k.a. libtorc

All-in-one web-based development environment for machine learning Getting Started • Features & Screenshots • Support • Report a Bug • FAQ • Known Issu

Geometry-Consistent Neural Shape Representation with Implicit Displacement Fields [project page][paper][cite] Geometry-Consistent Neural Shape Represe

tymon An AI Assistant More Than a Toolkit The reason for creating framework tymon is simple. making AI more like an assistant, helping us to complete

Gesture Controlled Video Game Detailed Blog : https://www.analyticsvidhya.com/blog/2021/06/gesture-controlled-video-game/ Introduction This project is

HyperPose is a library for building high-performance custom pose estimation applications.

XGBoost-Ray is a distributed backend for XGBoost, built on top of distributed computing framework Ray.

A mindmap summarising Machine Learning concepts, from Data Analysis to Deep Learning.

Densely Connected Time Delay Neural Network PyTorch implementation of Densely Connected Time Delay Neural Network (D-TDNN) in our paper "Densely Conne

NU-Wave — Official PyTorch Implementation NU-Wave: A Diffusion Probabilistic Model for Neural Audio Upsampling Junhyeok Lee, Seungu Han @ MINDsLab Inc

Neural Logic Inductive Learning This is the implementation of the Neural Logic Inductive Learning model (NLIL) proposed in the ICLR 2020 paper: Learn

Depth-supervised NeRF: Fewer Views and Faster Training for Free Project | Paper | YouTube Pytorch implementation of our method for learning neural rad

Rapid Neural Architecture Search by Learning to Generate Graphs from Datasets This is the official PyTorch implementation for the paper Rapid Neural A

**Codebase and data are uploaded in progress. ** VOLT(-py) is a vocabulary learning codebase that allows researchers and developers to automaticaly ge

Knodle (Knowledge-supervised Deep Learning Framework) - a new framework for weak supervision with neural networks. It provides a modularization for se

spacy-huggingface-hub: Push your spaCy pipelines to the Hugging Face Hub This package provides a CLI command for uploading any trained spaCy pipeline

Trilium Translation 中文说明 This repo provides a translation for the awesome Trilium Notes. Currently, I have translated Trilium Notes into Chinese. Test

MooGBT is a library for Multi-objective optimization in Gradient Boosted Trees. MooGBT optimizes for multiple objectives by defining constraints on sub-objective(s) along with a primary objective. The constraints are defined as upper bounds on sub-objective loss function. MooGBT uses a Augmented Lagrangian(AL) based constrained optimization framework with Gradient Boosted Trees, to optimize for multiple objectives.

Official PyTorch implementation of the preprint paper "Stylized Neural Painting", accepted to CVPR 2021.

Crypto-Currency-Predictor This machine-learning algorithm takes in data from the last 60 days and tries to predict tomorrow's price of any crypto you

The goal is to classify different birds species based on their songs/calls. Spectrograms have been extracted from the audio samples and used as features for classification.

Hangman game The Hangman game is a game whereby one person thinks of a word, which is kept secret from another person, who tries to guess the word one

Posture: Pose Tracking and Machine Learning for prescribing corrective suggestions to improve posture and form while exercising. This repository conta

This is my reading list for my PhD in AI, NLP, Deep Learning and more.

🤖 Scrape data from HTML websites automatically with Machine Learning

GPRGNN This is the source code for our ICLR2021 paper: Adaptive Universal Generalized PageRank Graph Neural Network. Hidden state feature extraction i

Balancing Training for Multilingual Neural Machine Translation Implementation of the paper Balancing Training for Multilingual Neural Machine Translat

REval Table of Contents Introduction Overview Requirements Installation Probing Usage Citation License 🎓 Introduction REval is a simple framework for

Part of the 9th place solution for the Bristol-Myers Squibb – Molecular Translation challenge translating images containing chemical structures into I

Implicit Representations of Meaning in Neural Language Models Preliminaries Create and set up a conda environment as follows: conda create -n state-pr

This repository contains FEDOT - an open-source framework for automated modeling and machine learning (AutoML). It can build custom modeling pipelines for different real-world processes in an automated way using an evolutionary approach. FEDOT supports classification (binary and multiclass), regression, clustering, and time series prediction tasks.

Azure Cloud Advocates at Microsoft are pleased to offer a 12-week, 24-lesson curriculum all about Machine Learning

R-Drop: Regularized Dropout for Neural Networks R-drop is a simple yet very effective regularization method built upon dropout, by minimizing the bidi

FastPitchFormant - PyTorch Implementation PyTorch Implementation of FastPitchFormant: Source-filter based Decomposed Modeling for Speech Synthesis. Qu

AnalyticMesh Analytic Marching is an exact meshing solution from neural networks. Compared to standard methods, it completely avoids geometric and top

SimulEval SimulEval is a general evaluation framework for simultaneous translation on text and speech. Requirement python = 3.7.0 Installation git cl

Machine Unlearning with SISA Lucas Bourtoule, Varun Chandrasekaran, Christopher Choquette-Choo, Hengrui Jia, Adelin Travers, Baiwu Zhang, David Lie, N

Recurrent Fast Weight Programmers This is the official repository containing the code we used to produce the experimental results reported in the pape

PPLNN is a Primitive Library for Neural Network is a high-performance deep-learning inference engine for efficient AI inferencing

pure-predict speeds up and slims down machine learning prediction applications. It is a foundational tool for serverless inference or small batch prediction with popular machine learning frameworks like scikit-learn and fasttext. It implements the predict methods of these frameworks in pure Python.

Graph4NLP Graph4NLP is an easy-to-use library for R&D at the intersection of Deep Learning on Graphs and Natural Language Processing (i.e., DLG4NLP).

A ready-to-use framework of latest models for structured (tabular) data learning with PyTorch. Applications include recommendation, CRT prediction, healthcare analytics, and etc.

A python library to build Model Trees with Linear Models at the leaves.

A data preprocessing package for time series data. Design for machine learning and deep learning.

Non-autoregressive Deep Learning-Based TTS Template This is a template for the Non-autoregressive TTS model. It contains Data Preprocessing Pipeline D

Meerkat makes it easier for ML practitioners to interact with high-dimensional, multi-modal data. It provides simple abstractions for data inspection, model evaluation and model training supported by efficient and robust IO under the hood.

EdMIPS is an efficient algorithm to search the optimal mixed-precision neural network directly without proxy task on ImageNet given computation budgets. It can be applied to many popular network architectures, including ResNet, GoogLeNet, and Inception-V3.

SNN_Calibration Pytorch Implementation of Spiking Neural Networks Calibration, ICML 2021 Feature Comparison of SNN calibration: Features SNN Direct Tr

AD-NeRF: Audio Driven Neural Radiance Fields for Talking Head Synthesis | Project Page | Paper | PyTorch implementation for the paper "AD-NeRF: Audio

Allennlp Integration for Shiba allennlp-shiab-model is a Python library that provides AllenNLP integration for shiba-model. SHIBA is an approximate re

Gamestonk Terminal is an awesome stock and crypto market terminal. A FOSS alternative to Bloomberg Terminal.

Objective of the repository is to learn and build machine learning models using Pytorch. 30DaysofML Using Pytorch

Soft DTW Loss Function for PyTorch in CUDA This is a Pytorch Implementation of Soft-DTW: a Differentiable Loss Function for Time-Series which is batch

Pretrained SOTA Deep Learning models, callbacks and more for research and production with PyTorch Lightning and PyTorch

What is Craxk ? Craxk is a UNIQUE AND NON-REPLICABLE Hash that uses data from the hardware where it is executed to form a hash that can only be reprod

The inductive bias of a neural network is largely determined by the architecture and the training algorithm. To achieve good generalization, how to effectively train a neural network is of great importance. We propose a novel orthogonal over-parameterized training (OPT) framework that can provably minimize the hyperspherical energy which characterizes the diversity of neurons on a hypersphere. See our previous work -- MHE for an in-depth introduction.

DeepProbLog DeepProbLog is an extension of ProbLog that integrates Probabilistic Logic Programming with deep learning by introducing the neural predic

Neural G2P to portuguese language Grapheme-to-phoneme (G2P) conversion is the process of generating pronunciation for words based on their written for

BRepNet: A topological message passing system for solid models This repository contains the an implementation of BRepNet: A topological message passin

WaveGrad2 - PyTorch Implementation PyTorch Implementation of Google Brain's WaveGrad 2: Iterative Refinement for Text-to-Speech Synthesis. Status (202

Home Install Documentation Slack Invite Cray Labs SmartSim SmartSim makes it easier to use common Machine Learning (ML) libraries like PyTorch and Ten

Break-It-Fix-It: Learning to Repair Programs from Unlabeled Data This repo provides the source code & data of our paper: Break-It-Fix-It: Unsupervised

Image Translation with ASAPNets Spatially-Adaptive Pixelwise Networks for Fast Image Translation, CVPR 2021 Webpage | Paper | Video Installation insta

This repository is the official PyTorch implementation of Meta-Balance. Find the paper on arxiv MetaBalance: High-Performance Neural Networks for Clas

Learning Neural Network Subspaces Welcome to the codebase for Learning Neural Network Subspaces by Mitchell Wortsman, Maxwell Horton, Carlos Guestrin,

Random Walk Graph Neural Networks This repository is the official implementation of Random Walk Graph Neural Networks. Requirements Code is written in

SmartSim makes it easier to use common Machine Learning (ML) libraries like PyTorch and TensorFlow, in High Performance Computing (HPC) simulations and workloads.

JittorVis - Visual understanding of deep learning model.

The `rtdl` library + The official implementation of the paper "Revisiting Deep Learning Models for Tabular Data"

An english representation of machine learning. Modify what you want, let us handle the rest. Overview Nylon is a python library that lets you customiz

ContextNet ContextNet has CNN-RNN-transducer architecture and features a fully convolutional encoder that incorporates global context information into