Neural Machine Translation (NMT), NMT Leave a comment

Machine Translation Weekly 94: Notes from WMT 2021

After the notes from EMNLP 2021, here is also an unsorted list of some observations from the Conference on Machine Translation. Facebook AI won in many translation directions (not at all in all of them) in the news task with a multilingual system. At the panel discussion about MT evaluation, Herman Nay expressed a controversial opinion: it does not matter what metric we use, the history of MT would be the same with any metric (that at least slightly correlates […]

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Python

Building a Neural Network & Making Predictions With Python AI

If you’re just starting out in the artificial intelligence (AI) world, then Python is a great language to learn since most of the tools are built using it. Deep learning is a technique used to make predictions using data, and it heavily relies on neural networks. This course will show you how to build a neural network from scratch. In a production setting, you would use a deep learning framework like TensorFlow or PyTorch instead of building your own neural […]

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Facebook NLP Research
NLP

Findings of the WMT 2021 Shared Task on Large-Scale Multilingual Machine Translation

November 8, 2021 By: Guillaume Wenzek, Vishrav Chaudhary, Angela Fan, Sahir Gomez, Naman Goyal, Somya Jain, Douwe Kiela, Tristan Thrush, Francisco Guzmán Abstract We present the results of the first task on Large-Scale Multilingual Machine Translation. The task consists on the many-to-many evaluation of a single model across a variety of source and target languages. This year, the task consisted on three different settings: (i) SMALLTASK1 (Central/South-Eastern European Languages), (ii) the SMALL-TASK2 (South East Asian Languages), and (iii) FULL-TASK (all […]

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Facebook NLP Research
NLP

Findings of the WMT 2021 Shared Task on Quality Estimation

November 8, 2021 By: Lucia Specia, Frédéric Blain, Marina Fomicheva, Chrysoula Zerva, Zhenhao Li, Vishrav Chaudhary, André F. T. Martins Abstract We report the results of the WMT 2021 shared task on Quality Estimation, where the challenge is to predict the quality of the output of neural machine translation systems at the word and sentence levels. This edition focused on two main novel additions: (i) prediction for unseen languages, i.e. zero-shot settings, and (ii) prediction of sentences with catastrophic errors. […]

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Games

Pokemon game made in Python with open ended requirements from Codecademy

Pokemon game made in Python with open ended requirements from Codecademy.This is one of my first projects utilizing OOP and classes! -This game is a 2 player game run from the terminal-Player can select their pokemon choices at the beginning-Then players can battle and perform 1 of 3 actions: attack opponent, use a potion, or switch out pokemon-intial release has some known bugs (they will be resolved in future iterations):-when pokemon is knocked out, trainer cannot reselect it. Currently, this […]

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metrics

Various code metrics for Python code

Radon is a Python tool that computes various metrics from the source code. Radon can compute: McCabe’s complexity, i.e. cyclomatic complexity raw metrics (these include SLOC, comment lines, blank lines, &c.) Halstead metrics (all of them) Maintainability Index (the one used in Visual Studio) Requirements Radon will run from Python 2.7 to Python 3.8 (except Python versions from 3.0 to 3.3) with a single code base and without the need of tools like 2to3 or six. It can also run […]

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Monitoring

Monitoring tool based on radon

Xenon is a monitoring tool based on Radon. It monitors your code’s complexity. Ideally, Xenon is run every time you commit code. Through command line options, you can set various thresholds for the complexity of your code. It will fail (i.e. it will exit with a non-zero exit code) when any of these requirements is not met. Installation With Pip: Or download the source and run the setup file (requires setuptools): $ python setup.py install Xenon is tested with all […]

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