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NLP PyTorch libraries; GAN tutorial; Jupyter tricks; TensorFlow things; Representation Learning; Making NLP more accessible; Michael Jordan essay; Reproducing Deep RL; Rakuten Data Challenge; NAACL Outstanding Papers

This newsletter has a lot of content, so make yourself a cup of coffee ☕️, lean back, and enjoy.This
April 23 · Issue #21 · View online
NLP News
This newsletter has a lot of content, so make yourself a cup of coffee ☕️, lean back, and enjoy.
This time, we have two NLP libraries for PyTorch; a GAN tutorial and Jupyter notebook tips and tricks; lots of things around TensorFlow; two articles on representation learning; insights on how to make NLP & ML more accessible; two excellent essays, one by Michael Jordan on challenges and opportunities for AI, the other by Amid Fish on reproducing a deep RL paper; the Rakuten Data Challenge; and lots of reading material including the NAACL Outstanding Papers.

Generative Adversarial Networks (GANs) are still as popular as ever.
Generative Adversarial Networks (GANs) are still as popular as ever.
Increasing data science productivity; founders of spaCy & Prodigy
Tools, implementations, and resources
Supporting Rapid Prototyping with a Toolkit
Pytorch NLP library based on FastAI
Alphabetical list of free datasets for NLP
Generative Adversarial Networks (GANs) in 50 lines of code (PyTorch)
Sentiment Classification from Keras to the Browser
Jupyter Tips, Tricks, Best Practices
Open-source entity coreference resolution systems
TensorFlow things
Introducing TensorFlow Probability
Building an Iris classifier with eager execution
Classifying text with TensorFlow Estimators
Representation learning
Goals and Principles of Representation Learning
What a Disentangled Net We Weave: Representation Learning in VAEs
Making NLP and ML accessible
Designing (and Learning From) a Teachable Machine
Technical Experts Need to Get Better at Telling Stories
Introducing Semantic Experiences with Talk to Books and Semantris
More articles and blog posts
Artificial Intelligence — The Revolution Hasn’t Happened Yet
Lessons Learned Reproducing a Deep Reinforcement Learning Paper
Machine Translation Without the Data
Rakuten Data Challenge
Evolved Policy Gradients
Designer Diary: The Search for AlphaMystica
Google Developers Blog: Text Embedding Models Contain Bias. Here's Why That Matters.
Industry insights
How Google Plans To Use AI To Reinvent The $3 Trillion US Healthcare Industry
Algorithmic Impact Assessments: A Practical Framework for Public Agency Accountability
Supervised Word Vectors from Scratch in Rasa NLU
Paper picks
NAACL-HLT 2018 Outstanding Papers
Delete, Retrieve, Generate: A Simple Approach to Sentiment and Style Transfer (NAACL-HLT 2018)
Detecting Linguistic Characteristics of Alzheimer's Dementia by Interpreting Neural Models (NAACL-HLT 2018)
Multi-Reward Reinforced Summarization with Saliency and Entailment (NAACL-HTL 2018)
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