Neural Machine Translation (NMT) tutorial with OpenNMT-py

Last update: Jan 09, 2023

Overview

OpenNMT-py Tutorial

Neural Machine Translation (NMT) tutorial with OpenNMT-py. Data preprocessing, model training, evaluation, and deployment.

Fundamentals

Data Processing (notebook, repository)
NMT Model Training with OpenNMT-py (notebook)
Translation/Inference with CTranslate3 (code)
MT Evaluation with BLEU (tutorial, repository)
Simple Web UI (tutorial, repository)

Advanced Topics

Running TensorBoard with OpenNMT (tutorial)
Low-Resource Neural Machine Translation (tutorial)
Domain Adaptation with Mixed Fine-tuning (tutorial)
Overview of Domain Adaptation Techniques (tutorial)
Multilingual Machine Translation (tutorial)

Owner

Yasmin Moslem

Machine Translation Researcher

GitHub Repository

Highly interpretable classifiers for scikit learn, producing easily understood decision rules instead of black box models

Highly interpretable, sklearn-compatible classifier based on decision rules This is a scikit-learn compatible wrapper for the Bayesian Rule List class

482 Nov 19, 2022

List of Data Science Cheatsheets to rule the world

Data Science Cheatsheets List of Data Science Cheatsheets to rule the world. Table of Contents Business Science Business Science Problem Framework Dat

11.7k Dec 30, 2022

Time series forecasting with PyTorch

Our article on Towards Data Science introduces the package and provides background information. Pytorch Forecasting aims to ease state-of-the-art time

2.5k Jan 02, 2023

Petastorm library enables single machine or distributed training and evaluation of deep learning models from datasets in Apache Parquet format. It supports ML frameworks such as Tensorflow, Pytorch, and PySpark and can be used from pure Python code.

Petastorm Contents Petastorm Installation Generating a dataset Plain Python API Tensorflow API Pytorch API Spark Dataset Converter API Analyzing petas

1.6k Dec 31, 2022

Neural Machine Translation (NMT) tutorial with OpenNMT-py

Related tags

Overview

OpenNMT-py Tutorial

Fundamentals

Advanced Topics

Owner

Yasmin Moslem

Highly interpretable classifiers for scikit learn, producing easily understood decision rules instead of black box models

List of Data Science Cheatsheets to rule the world

Time series forecasting with PyTorch

Petastorm library enables single machine or distributed training and evaluation of deep learning models from datasets in Apache Parquet format. It supports ML frameworks such as Tensorflow, Pytorch, and PySpark and can be used from pure Python code.

Implementation of deep learning models for time series in PyTorch.

Machine learning template for projects based on sklearn library.

A model to predict steering torque fully end-to-end

🎛 Distributed machine learning made simple.

Evidently helps analyze machine learning models during validation or production monitoring

This is a Cricket Score Predictor that predicts the first innings score of a T20 Cricket match using Machine Learning

Kaggle Competition using 15 numerical predictors to predict a continuous outcome.

Forecasting prices using Facebook/Meta's Prophet model

A comprehensive repository containing 30+ notebooks on learning machine learning!

A modular active learning framework for Python

K-Means clusternig example with Python and Scikit-learn

Deep Survival Machines - Fully Parametric Survival Regression

A pure-python implementation of the UpSet suite of visualisation methods by Lex, Gehlenborg et al.

Repositório para o #alurachallengedatascience1

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

A collection of machine learning examples and tutorials.