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Prikvačeni tweet
As promised, here is the first super clean notebook showcasing
@TensorFlow 2.0. An example of end-to-end DL with interpretability. Cc:@fchollet@random_forests@DynamicWebPaige https://colab.research.google.com/drive/1xM6UZ9OdpGDnHBljZ0RglHV_kBrZ4e-9 … PS: Wait for more!Prikaži ovu nitHvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
Aakash Kumar Nain proslijedio/la je Tweet
Some teaching material that covers some of this (in code exercises)https://github.com/ogrisel/text-mining-class …
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Aakash Kumar Nain proslijedio/la je Tweet
Multi-Channel Attention Selection GANs for Guided Image-to-Image Translation pdf: https://arxiv.org/pdf/2002.01048.pdf … abs: https://arxiv.org/abs/2002.01048 github: https://github.com/Ha0Tang/SelectionGAN …pic.twitter.com/Feq85Vbitk
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Aakash Kumar Nain proslijedio/la je Tweet
Want to code your own realtime object detection
#Python app with#JetsonNano? Be sure to check out this hands-on tutorial.https://lnkd.in/e9PuEiVHvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
Aakash Kumar Nain proslijedio/la je TweetHvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi
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Aakash Kumar Nain proslijedio/la je Tweet
Fixmatch: code for training on Imagenet dataset is released and available here: https://github.com/google-research/fixmatch/tree/master/imagenet … https://arxiv.org/abs/2001.07685 by Kihyuk Sohn
@D_Berthelot_ML@chunliang_tw@ZizhaoZhang Nicholas Carlini@ekindogus@alexey2004@Han_Zhang_@colinraffelHvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
Aakash Kumar Nain proslijedio/la je Tweet
We're having a Keras community meeting this Friday. If you want to make a Keras-related announcement or short presentation (~2 min) at the meeting, please send it to me by email and I'll include you.
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If this isn't the best tweet, Idk what is!https://twitter.com/oscarewilde/status/794969497602027520 …
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Aakash Kumar Nain proslijedio/la je Tweet
Check out the comments on the Facebook post for thoughts by Jitendra Malik, Alyosha Efros, Michael Black and othershttps://twitter.com/CSProfKGD/status/1224005645965369349 …
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Aakash Kumar Nain proslijedio/la je Tweet
PyPI downloads for TensorFlow (and its closest competitor, added for scale). Notice how it starts jumping after the release of TF 2.0 late last year (the short gap afterwards is the holiday break) Up and to the right
pic.twitter.com/Tlltw40hMO
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The biggest reasons why PyTorch became so popular on
@kaggle 1. Amazing model zoo. Very imp to start with a pretrained model in any comp based on NNs. 2. Compared to TF 1.x, writing models in it felt like writing C++ vs Pythonhttps://twitter.com/antgoldbloom/status/1224504654886658048 …
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Aakash Kumar Nain proslijedio/la je Tweet
Googler
@arvind_io asks a good question here, so I'll share my thoughts on Meena in a short thread. (1/6)https://twitter.com/arvind_io/status/1224045219827478528 …Prikaži ovu nitHvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
Aakash Kumar Nain proslijedio/la je Tweet
Finally watched
@anthonypjshaw's@pycon talk, "Writing simpler and more maintainable Python" today. Some great visuals and analogies in this talk!
I love the complexity mountain range, the functionality/users table, and the gravity of complexity. 
https://www.youtube.com/watch?v=dqdsNoApJ80 …Hvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
Aakash Kumar Nain proslijedio/la je Tweet
following my three-strikes-rule of "if you answer the same question three times in a short period write it down"; here's a simple example of loss masking for sequences with a custom training loop in tf2.0https://colab.research.google.com/drive/1ezRsZnNyIRXC1MFabsyXtDMgD6eMSc9n …
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Hvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi
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Aakash Kumar Nain proslijedio/la je Tweet
py-sanity: Opinionated Coding Guidelines and Best Practices in Python
#pythonhttps://github.com/rednafi/py-sanity …Hvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
Aakash Kumar Nain proslijedio/la je Tweet
Success: I trained ResNet-50 on imagenet to 75.9% top-1 accuracy in 3.51 minutes using a 512-core TPUv3. (480,000 images per second. 224x224 res JPG.) Before you think highly of me, all I did was run Google’s code. It was hard though. Logs: https://tensorboard.dev/experiment/jsDrRUynRXyw6dC2Fzpy4g …pic.twitter.com/E6b3cMD5r0
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Aakash Kumar Nain proslijedio/la je Tweet
A full build of Autopilot neural networks involves 48 networks that take 70,000 GPU hours to train. Together, they output 1,000 distinct tensors (predictions) at each timestep. This is what a Tesla autopilot sees [source: https://buff.ly/2OhFA5B ]pic.twitter.com/mNLtrobk8U
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Aakash Kumar Nain proslijedio/la je Tweet
Very excited to share "Learning Discrete Distributions by Dequantization" (https://arxiv.org/abs/2001.11235 ) in collaboration with
@TacoCohen and@jmtomczak, from my internship at@Qualcomm. We explore different methods and distributions for dequantization and reach 3.06 bpd on CIFAR10.pic.twitter.com/IGJa7YV8YG
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Aakash Kumar Nain proslijedio/la je Tweet
FIS-Nets: Full-image Supervised Networks for Monocular Depth Estimation. http://arxiv.org/abs/2001.11092 pic.twitter.com/CIPZnot0ky
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