Python Machine-translation-models Resources

PlainML Painless Machine Learning Library for python based on scikit-learn. Install pip install plainml Example from plainml import KnnModel, load_ir

NaturalCC NaturalCC is a sequence modeling toolkit that allows researchers and developers to train custom models for many software engineering tasks,

smc.covid smc.covid is an R package related to the paper A sequential Monte Carlo approach to estimate a time varying reproduction number in infectiou

CoINN: Correlated-informed neural networks: a new machine learning framework to predict pressure drop in micro-channels Accurate pressure drop estimat

Readme File for "Using Machine Learning to Test Causal Hypotheses in Conjoint Analysis" by Ham, Imai, and Janson. (2022) All scripts were written and

JASS: Japanese-specific Sequence to Sequence Pre-training for Neural Machine Translation This the repository for this paper. Find extensions of this w

User-centered Regression An Approach to Explore Logistic Regression Models This tool applies the potential of Attribute-RadViz in identifying correlat

CNN-Filter-DB An Empirical Investigation of Model-to-Model Distribution Shifts in Trained Convolutional Filters Paul Gavrikov, Janis Keuper Paper: htt

Explore the Expression: Facial Expression Generation using Auxiliary Classifier Generative Adversarial Network This is the official implementation of

Interpretable Control Exploration and Counterfactual Explanation (ICE) on StyleGAN Which Style Makes Me Attractive? Interpretable Control Discovery an

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

Unsupervised Audio Source Separation Using Differentiable Parametric Source Models This is the source code for the experiments related to the paper Un

AI for TSP Competition Goal In the AI for TSP competition we try to solve optimization problems using machine learning. The competition will be hosted

How robust are discriminatively trained zero-shot learning models? This repository contains the PyTorch implementation of our paper How robust are dis

Variational Model Inversion Attacks Kuan-Chieh Wang, Yan Fu, Ke Li, Ashish Khisti, Richard Zemel, Alireza Makhzani Most commands are in run_scripts. W

This repository contains Pytorch evaluation code, training code and pretrained models for the following projects: SPACH (A Battle of Network Structure

CSPML (crystal structure prediction with machine learning-based element substitution) CSPML is a unique methodology for the crystal structure predicti

Tackling data scarcity in Speech Translation using zero-shot multilingual Machine Translation techniques This repository is derived from the NMTGMinor

Prabhupadavani: A Code-mixed Speech Translation Data for 25 languages Code for the paper titled "Prabhupadavani: A Code-mixed Speech Translation Data

shap-hypetune A python package for simultaneous Hyperparameters Tuning and Features Selection for Gradient Boosting Models. Overview Hyperparameters t

We provide a notebook that shows how to import the IITB English-Hindi Parallel Corpus from the HuggingFace datasets repository. The notebook also shows how to segment the corpus using BPE tokenization which can be used to train an English-Hindi MT System.

The purpose of this project is create a classification model capable of accurately predicting the price of secondhand cars. The data used for model building is open source and has been added to this repository. Most packages used are usually pre-installed in most developed environments and tools like collab, jupyter, etc. This can be useful for people looking to enhance the way the code their predicitve models and efficient ways to deal with tabular data!

This model involves Insurance bill prediction, which was subsequently deployed on Heroku PaaS

The purpose of this project is create a predictive model capable of identifying the probability of a person securing an admit based on their personal profile parameters. Simplified visualisations have been created for understanding the data. 80% accuracy was achieved on the test set.

Audio Source Separation is the process of separating a mixture into isolated sounds from individual sources (e.g. just the lead vocals).

Machine_Learning Election Exit Poll Prediction and U.S.A Presidential Speech Analysis using Machine Learning This project is based on 2 case-studies:

Description This library provides an abstraction to perform Model Versioning using Weight & Biases. Features Version a new trained model Promote a mod

Semantic Segmentation Easy to use and customizable SOTA Semantic Segmentation models with abundant datasets in PyTorch Features Applicable to followin

Twitter-News-Summarizer Twitter bot that uses NLP models to summarize news articles referenced in a user's twitter timeline 1.) Extracts all tweets fr

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.

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

Neural Tangent Generalization Attacks (NTGA) ICML 2021 Video | Paper | Quickstart | Results | Unlearnable Datasets | Competitions | Citation Overview

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

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

Hello from magnus Magnus provides four capabilities for data teams: Compute execution plan: A DAG representation of work that you want to get done. In

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

Self-supervised learning (SSL) is a method of machine learning. It learns from unlabeled sample data. It can be regarded as an intermediate form between supervised and unsupervised learning.

Emotion AI This is a Deep Leaning API for classifying emotions from human face and human audios. Starting the server To start the server first you nee

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

Yu-Gi-Oh! Master Duel translation script

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

Keepsake Version control for machine learning. Keepsake is a Python library that uploads files and metadata (like hyperparameters) to Amazon S3 or Goo

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

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

Shield: This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License. Deep Learning to Improve Breast

Detection-aided liver lesion segmentation Here we present the implementation in TensorFlow of our work about liver lesion segmentation accepted in the

Medical Data for Machine Learning This is a curated list of medical data for machine learning. This list is provided for informational purposes only,

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

Note: Robosat is neither maintained not actively developed any longer by Mapbox. See this issue. The main developers (@daniel-j-h, @bkowshik) are no l

Awesome Satellite Imagery Datasets List of aerial and satellite imagery datasets with annotations for computer vision and deep learning. Newest datase

MLND-Capstone My capstone project for Udacity's Machine Learning Nanodegree Lane Detection with Deep Learning In this project, I use a deep learning-b

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

Segment axon and myelin from microscopy data using deep learning. Written in Python. Using the TensorFlow framework. Based on a convolutional neural network architecture. Pixels are classified as either axon, myelin or background.

Natural Posterior Network This repository provides the official implementation o

Built a deep neural network (DNN) that functions as an end-to-end machine translation pipeline. The pipeline accepts english text as input and returns the French translation.

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

Machine-Learning with python (jupyter) 머신러닝 야학 작심 10일과 쥬피터 노트북 기반 데이터 사이언스 시작 들어가기전 https://nbviewer.org/ 페이지를 통해서 쥬피터 노트북 내용을 볼 수 있다. 위 페이지에서 현재 레포 기

Laporan Proyek Machine Learning - Azhar Rizki Zulma Project Overview Domain proyek yang dipilih dalam proyek machine learning ini adalah mengenai hibu

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

Video-Captioning - A machine Learning project to generate captions for video frames indicating the relationship between the objects in the video

Personal Finance Forecaster - An AI tool for forecasting personal expenses

MasterDuelTranslate(Use Ygo Card DataBase,belong win32 window shot & image match)

Synthetic data need to preserve the statistical properties of real data in terms of their individual behavior and (inter-)dependences. Copula and functional Principle Component Analysis (fPCA) are statistical models that allow these properties to be simulated (Joe 2014). As such, copula generated data have shown potential to improve the generalization of machine learning (ML) emulators (Meyer et al. 2021) or anonymize real-data datasets (Patki et al. 2016).

A feature store is a data storage system for data science and machine-learning. It can store raw data and also transformed features, which can be fed straight into an ML model or training script.

package tests docs license stats support This repository contains FEDOT - an open-source framework for automated modeling and machine learning (AutoML

Optuna is an automatic hyperparameter optimization software framework, particularly designed for machine learning. It features an imperative, define-by-run style user API.

ParaMonte is a serial/parallel library of Monte Carlo routines for sampling mathematical objective functions of arbitrary-dimensions, in particular, the posterior distributions of Bayesian models in data science, Machine Learning, and scientific inference, with the design goal of unifying the automation (of Monte Carlo simulations), user-friendliness (of the library), accessibility (from multiple programming environments), high-performance (at runtime), and scalability (across many parallel processors).

visualize_ML visualize_ML is a python package made to visualize some of the steps involved while dealing with a Machine Learning problem. It is build

Author Ayanwoye, Gideon Ayandele - [email protected] SOLUTION TO HAMOYE STAGE A QUIZ INTRODUCTION TO PYTHON FOR MACHINE LEARNING The dataset is prov

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

About scikit-learn is a python module for machine learning built on top of numpy / scipy. The purpose of the scikit-learn-tutorial subproject is to le

Sentiment Classification using WSD, Maximum Entropy & Naive Bayes Classifiers

climin climin is a Python package for optimization, heavily biased to machine learning scenarios distributed under the BSD 3-clause license. It works

Dive into Machine Learning Hi there! You might find this guide helpful if: You know Python or you're learning it 🐍 You're new to Machine Learning You

Suiron Machine Learning for RC Cars Prediction visualization (green = actual, blue = prediction) Click the video below to see it in action! Dependenci

This repository contains Jupyter notebooks implementing the algorithms found in the book and summary of the textbook.

Neuron class provides LNU (Linear Neural Unit), QNU (Quadratic Neural Unit), RBF (Radial Basis Function), MLP (Multi Layer Perceptron), MLP-ELM (Multi Layer Perceptron - Extreme Learning Machine) neurons learned with Gradient descent or LeLevenberg–Marquardt algorithm

Home Credit Default Risk: Open Solution This is an open solution to the Home Credit Default Risk challenge 🏡 . More competitions 🎇 Check collection

Google AI Open Images - Object Detection Track: Open Solution This is an open solution to the Google AI Open Images - Object Detection Track 😃 More c

TGS Salt Identification Challenge This is an open solution to the TGS Salt Identification Challenge. Note Unfortunately, we can no longer provide supp

Airbus Ship Detection Challenge This is an open solution to the Airbus Ship Detection Challenge. Our goals We are building entirely open solution to t

bookmarkarchiver Python script that archives all of your bookmarks on the Internet Archive. Supports all major browsers. bookmarkarchiver uses the off

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

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

Computational Optimal Transport for Machine Learning Reading Group Over the last few years, optimal transport (OT) has quickly become a central topic

Deep learning Udacity Course Deep Learning Topics with Computer Vision & NLP for the AWS Machine Learning Engineer Nanodegree Program Tasks are mostly

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

Predicting Keystrokes using an Audio Side-Channel Attack and Machine Learning My

Fast Forward Computer Vision: train models at a fraction of the cost with accele

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.