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This video explains
@GoogleAI 's amazing new Meena chatbot! An Evolved Transformer with 2.6B parameters on 341 GB / 40B words of conversation data to achieves remarkable chatbot performance! "Horses go to Hayvard!" https://youtu.be/STrrlLG15OY#100DaysOfMLCodeHvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
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If you want to learn about privacy-preserving machine learning, then there is no better resource than this step-by-step notebook tutorial by
@iamtrask. From the basics of private deep learning to building secure ML classifiers using PyTorch & PySyft.https://github.com/OpenMined/PySyft/tree/master/examples/tutorials …Hvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
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Backpropagation and labeled data are the bread and butter of deep learning. But recent research from the University of Amsterdam suggests neither is necessary to train effective neural networks to represent complex data: http://bit.ly/38wLUOj pic.twitter.com/Ok6IV7QLWZ
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Keras inventor Chollet charts a new direction for AI: a Q&A | ZDNet https://zd.net/36mOcit
#AI#DeepLearning#ML#DataSciencepic.twitter.com/lxSQEykLjm
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The history of Amazon's recommendation algorithmhttps://www.amazon.science/the-history-of-amazons-recommendation-algorithm …
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Hvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi
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Eric Schmidt on state-of-the-art in AI: - Pretty much all interesting AI approaches involve GANs in the middle - Speech and images are solved problems - TensorFlow is being used by everyone - We know data has bias. You don't need to yell that as a new fact.
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AI curriculum
CS231n: CNNs for Visual Recognition, Stanford | Spring 2019
http://cs231n.stanford.edu/
CS224n: NLP with Deep Learning, Stanford | Winter 2019
http://web.stanford.edu/class/cs224n/index.html#schedule …
CS285: Deep Reinforcement Learning, UC Berkeley | Fall 2019https://www.youtube.com/playlist?list=PLkFD6_40KJIwhWJpGazJ9VSj9CFMkb79A …Hvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
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The remaining lectures from my Natural Language Understanding course are now up: https://www.youtube.com/playlist?list=PLoROMvodv4rObpMCir6rNNUlFAn56Js20 … I have highest hopes for the contextual word reps one; I tried to methodically walk through those models with diagrams, to supplement the great tutorials already out there.
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A Fair Comparison Study of XLNet and BERT with Large Models:https://medium.com/@xlnet.team/a-fair-comparison-study-of-xlnet-and-bert-with-large-models-5a4257f59dc0 …
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XLNet: Generalized Autoregressive Pretraining for Language Understanding: outperforming BERT on 20 tasks (SQuAD, GLUE, sentiment analysis), while integrating ideas from Transformer-XL: arxiv: https://arxiv.org/abs/1906.08237 code + pretrained models: https://github.com/zihangdai/xlnet https://twitter.com/quocleix/status/1141511813709717504 …
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今日はこれ見てる。Interpretabilityの技術はSaliency Maps、Occulusion Sensitivity、Class Activation Mapsがある。 Stanford CS230: Deep Learning | Autumn 2018 | Lecture 7 - Interpretabili... https://youtu.be/gCJCgQW_LKc
@YouTubeさんからHvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
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PyTorch 101 Part 1: Understanding Graphs, Automatic Differentiation and Autogradhttps://blog.paperspace.com/pytorch-101-understanding-graphs-and-automatic-differentiation/ …
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A few weeks ago, a friend of mine asked me "Which papers can I read to catch up with the latest trends in modern NLP?".

I compiled a list of papers and resources for him
and thought it would be great to share it!https://medium.com/huggingface/the-best-and-most-current-of-modern-natural-language-processing-5055f409a1d1 …Hvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
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New NLP Newsletter: Marvel, Stanford & CMU NLP Playlists, Voynich, Bitter Lesson Vol. 2, ICLR 2019, Dialogue Demos http://newsletter.ruder.io/archive/173432 (via
@revue)Hvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
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Introducing our new library FastBert. It will helps developers and data scientists develop and deploy BERT based model. Thank you
#HuggingFace and#fastaihttps://link.medium.com/EbGOD0KhLWHvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
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Pixel-aligned Implicit Function (PIFu), a new memory efficient, fully-convolutional 3D representation for recovering a fully textured surface of a clothed person from a single or multi-view image! https://shunsukesaito.github.io/PIFu/ With Shunsuke S, Zeng H,
@r_natsume, Shigeo M,@HaoLi81pic.twitter.com/JgxHH3KsjLPrikaži ovu nitHvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
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An Introduction to Deep Reinforcement Learning (PDF book manuscript, Nov 2018) https://arxiv.org/abs/1811.12560
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Course 2 of the
@deeplearningai_@TensorFlow Specialization is now available on@Coursera! You’ll learn how to use TF to handle real-world data, avoid overfitting w/augmentation and dropout, and more. You can take the course for $49 or audit it for free:https://www.coursera.org/learn/convolutional-neural-networks-tensorflow …Hvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
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Slides & articles from the Workshop on Responsible Recommendation Systems
@fatrecsys https://piret.gitlab.io/fatrec2018/program/ …pic.twitter.com/HrRqaLDMaN
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