Teaching AI systems to learn language from letters, not words
http://bit.ly/2LDrP1v

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The Past, Present, and Future of AI Art
http://bit.ly/2JNz9Fv

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Introducing long-form question answering
http://bit.ly/2ZgqQYi

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A 2019 Guide to Object Detection - Heartbeat
http://bit.ly/2K0eyy4

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Why random forests outperform decision trees - Towards Data Science
http://bit.ly/2SOm9Ck

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Google AI Blog: Robust Neural Machine Translation
http://bit.ly/2YkJzVZ

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Microsoft makes AI debugging and visualization tool TensorWatch open source - Microsoft Research
http://bit.ly/2yyEQRa

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Recommendation System Dengan Python : Collaborative Filtering (Part 3)
http://bit.ly/2ZtnWiU
author: @zheaven07

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Keras Tuner - A Hyperparameter Tuner for Keras
http://bit.ly/2KdbGOm

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Advances in Conversational AI
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RoBERTa: An optimized method for pretraining self-supervised NLP systems
http://bit.ly/2MHTxtx

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How to Make Face Clustering Using Python
http://bit.ly/33al0tT
author @Hervindphil

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Where Journalism meets data
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Visualization Tools and Resources, July 2019 Roundup
http://bit.ly/2OHtQvT

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How to Run PyTorch with TPUs
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New Releases: PyTorch 1.2, torchtext 0.4, torchaudio 0.3, and torchvision 0.4
http://bit.ly/2MZ7AeD

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TURING LECTURES - Presented by each winner on the topic of their choice at a forum
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3000 Years of Algorithmic Rituals: The Emergence of AI from the Computation of Space
http://bit.ly/2N6ogAX


EfficientNet-EdgeTPU: Creating Accelerator-Optimized Neural Networks with AutoML
http://bit.ly/2KCZZzo

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The Top 10 in Podcasts
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PyTorch 1.2 released as Global Summer Hackathon kicks off
http://bit.ly/2YKrzoh

Science at Uber: Applying Artificial Intelligence at Uber
https://ubr.to/304kLyy

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NVIDIA train BERT-Large within 53 mins using ~1500 GPUs
http://bit.ly/31LsQZr

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ACL Annual Conference 2020
https://acl2020.org/

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Must-read papers on graph neural networks (GNN)
http://bit.ly/2Z7WHxg

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Science at Uber: Making a Real-world Impact with Data Science
https://ubr.to/2MtWRJD

GPT-2: 6-Month Follow-Up
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New advances in natural language processing to better connect people
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Ludwig - Another AutoML
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A Detailed Guide to 7 Loss Functions for Machine Learning Algorithms with Python Code
http://bit.ly/321uQwD

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