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METHOD ACTING: Acting is very real, more real than the clump of habits you have come to recognize as your personality. Acting requires you to be conscious every moment, lest you stop acting and start "habiting"..
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"We achieved an overall accuracy of 94.5%, more than 4.5% of an increase on the previous state-of-the-art"; classifying the patterns in 18,577 Scanning Electron Microscope imageshttps://twitter.com/Iain_Keaney/status/1224420379076198402 …
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Teaching Deep Unsupervised Learning (2nd edition) at
@UCBerkeley this semester. You can follow along here: https://sites.google.com/view/berkeley-cs294-158-sp20/home … Instructor Team:@peterxichen ,@Aravind7694 ,@hojonathanho , Wilson Yan, Alex Li,@pabbeel YouTube, PDF, and Google Slides for ease of re-usepic.twitter.com/VTvffsEjHf
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This repo is full of amazing awesomeness. I don't know of anything else like it. Independent refactored carefully tested implementations of modern CNNshttps://twitter.com/wightmanr/status/1224178577593241602 …
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Through this great story from James Briggs, a computational physicist turned data scientist, I came across his totally amazing deep learning notes, which are some of the best I've seen: http://jimypbr.github.io/2019/09/fast-ai-lesson-6-notes …pic.twitter.com/gzvmCrJpXr
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Recently, I am working on moving machine learning models to production. So I made a detailed guide on how to do this properly! Instead of a minimal example, I demonstrate best practices with state of the art tools. Enjoy!
#fastapi#docker#githubactionshttps://towardsdatascience.com/how-to-properly-ship-and-deploy-your-machine-learning-model-8a8664b763c4 …Hvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
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New paper: Towards a Human-like Open-Domain Chatbot. Key takeaways: 1. "Perplexity is all a chatbot needs" ;) 2. We're getting closer to a high-quality chatbot that can chat about anything Paper: https://arxiv.org/abs/2001.09977 Blog: https://ai.googleblog.com/2020/01/towards-conversational-agent-that-can.html …pic.twitter.com/5SOBa58qx3
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Interesting mini thread on a possibly under-used approach for training modelshttps://twitter.com/scottlegrand/status/1221239687311810561 …
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I wrote a blog post about the machine reading comprehension demo I recently shared. Tutorial notebook at the end if you want to train your own!
@huggingface@GoogleAI#NLP#DeepLearninghttps://spark64.com/post/machine-comprehension …Hvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
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Brought to you by our very own Mathijs, Verna, Elia and
@_dieuwke_!https://twitter.com/Thom_Wolf/status/1219724316260126721 …
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Help me Twitter. Best (reasonably technical) math/science podcasts?
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Hypothesis on how language models workhttps://www.reddit.com/r/MachineLearning/comments/eqrd97/d_hypothesis_on_how_language_models_work/ …
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Great intro to the modern landscape of Deep Learning &
#nlproc by@lexfridman@MIT. Including sweet mentions of the models inside@huggingface transformers, write with transformers &@seb_ruder's NLP progress repo! https://youtu.be/0VH1Lim8gL8?t=1114 … https://youtu.be/0VH1Lim8gL8?t=1282 …pic.twitter.com/pB4iyeCuAE
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More cool stuff from Facebook AI!!https://twitter.com/facebookai/status/1217505527585890304 …
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"During 2018 I achieved a Kaggle Master badge (...). Very often I found myself re-using most of the old pipelines over and over again. At some point it crystallized into this repository." PyTorch extensions for fast R&D prototyping and Kaggle farminghttps://github.com/BloodAxe/pytorch-toolbelt …
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Distributing your workload across multiple
#GPUs with BlazingSQL is easy & everything you need is already installed by default! Simply pass in the Dask Client of your LocalCUDACluster into BlazingContext upon initialization and you're good to go!#Distributed#SQL#Pythonpic.twitter.com/CePPHlVMCl
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Tried mixed precision yet? Took 10 min to set up and my model runs almost 2x faster with same results. Vars and grads are still 32 bits so it usually doesn't affect predictive performance. E.g. in TF2, set option and make all input to your layers float16 (data, RNN states, ..):pic.twitter.com/Dk7berTCGF
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Current image datasets are getting very large and pre-training on them is time consuming. We are releasing Neural Data Server (NDS), a search engine for transfer learning data!
@yanxi0830@davidjesusacu#UofT Webservice: http://aidemos.cs.toronto.edu/nds Paper: https://arxiv.org/abs/2001.02799 pic.twitter.com/i5od82gekdHvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
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“Meet AdaMod: a new deep learning optimizer with memory” by Less Wrighthttps://link.medium.com/CfAtYwooa3
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Deep learning achieves perfect anomaly detection on 108,308 retinal images including unlearned diseases https://deepai.org/publication/deep-learning-achieves-perfect-anomaly-detection-on-108308-retinal-images-including-unlearned-diseases … by Ayaka Suzuki et al.
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A Sober Look at Bayesian Neural Networks L: https://jacobbuckman.com/2020-01-17-a-sober-look-at-bayesian-neural-networks/ … C: https://news.ycombinator.com/item?id=22082860 …
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