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PyTorch 0.4.0, Google Brain Tokyo, QuickNLP, Multilingual NLU, PeerRead dataset, PyTorch GAN, ML Openness, SGD Earth, DL for Alzheimer's Detection, ...

Welcome to the 12th Issue of the NLP Newsletter! Here is this week’s notable NLP news!

On People…
A statement has been circulating for ML people to sign against "closed access or author-fee publication" (We definitely signed! Let's keep ML research open) - Link
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Are emojis ruining the way young people use the English language to communicate? - Link

Hands down one of the best AI essays of the year by Professor Michael Jordan (Artificial Intelligence — The Revolution Hasn’t Happened Yet) - Link

Multilingual natural language understanding by Spacy (Video) - Link
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Why technical experts need to get better at telling stories - Link

Bias in word embeddings? (Google Research Blog) - Link
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On Education and Research…
Paper revisiting on how to make better choices with batch training in neural networks - Link

Paper discussing when and why word embeddings are good for neural machine translation - Link

Olive Oil is Made of Olives, Baby Oil is Made for Babies (Paper Summary) - Link
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Paper discusses how to go about conducting evaluation on "Deep Semi-Supervised Learning Algorithms" - Link

Using deep learning to detect linguistic cues of Alzheimer’s disease patients - Link
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Summary of interesting NLP Papers and Research (Fast and easy reads!) - Link

How Natural Language Inference Models “Game” the Task of Learning - Link

On Code and Data...
PyTorch 0.4.0 is released (Trade-off memory for compute, Windows support, 24 distributions with cdf, variance etc., dtypes, zero-dimensional Tensors, Tensor-Variable merge, faster distributed, perf and bug fixes, CuDNN 7.1) - Link

Quick NLP is a deep learning nlp library inspired by the library - Link

"PeerRead is a dataset of scientific peer reviews available to help researchers study this important artifact" - Link

Executing gradient descent on Earth - Link

GANs in 50 lines of code with PyTorch - Link

A guide to conducting sequence prediction (one of the hottest trends in deep learning) with Python - Link
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Alphabetical list of NLP datasets - Link

On Industry…
Google expands Google Brain team in Tokyo (now accepting applications) - Link

OpenAI holds transfer learning contest using Sonic The Hedgehog game - Link

Very nice video tutorial by Uber AI Labs on "Measuring the Intrinsic Dimension of Objective Landscapes" - Link

How NLP offers a bright future for airlines and passengers - Link

Scientists plan huge European AI hub to compete with US - Link

Quote of the Week...
"We see no role for closed access or author-fee publication in the future of machine learning research and believe the adoption of this new journal as an outlet of record for the machine learning community would be a retrograde step." (@tdietterich)

Visualization of the Week...
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"Sorry officer, my car has old version of TensorFlow, I'll update it tonight" - Link

Worthy Mentions…
Implementing YOLO v3 with PyTorch - Link
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NLP News by Sebastian Ruder (Issue 21) - Link

Speakeasy - Fun article explaining how aliens can help our digital assistants with linguistic assistance (sounds mostly fictional but it's actually very insightful) - Link

A nice summarized version of the MIT Probability course - Link

Paper on the Theory of Mind - Link

Why deep learning is perfect for NLP - Link

5 Fantastic Practical Natural Language Processing Resources - Link

Our previous newsletter (Issue 11) - Link

Message from the Editor
Hello everyone! Thanks for the massive support you have given to this newsletter. I realized the tremendous good it can do for experts in the field and those who are beginning. The previous newsletter did so well that I got excited to see how much people were interested in such newsletter (3K+ views). I hope to keep bringing more of the best of NLP and ML news in the weeks that follow. Also, come over to @omarsar0 and say hi!

If you spot any errors or inaccuracies in this newsletter please open an issue.
Submit a pull request if you would like to add important NLP news here.