Recent Advances in Language Model Fine-tuning

By Sebastian Ruder:

https://ruder.io/recent-advances-lm-fine-tuning/
@Machine_learn

Machine Learning for Time Series Forecasting with Python (2020)

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Lyra: A New Very Low Bitrate Codec for Speech Compression


http://ai.googleblog.com/2021/02/lyra-new-very-low-bitrate-codec-for.html

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Unbiased Teacher for Semi-Supervised Object Detection

Github: https://github.com/facebookresearch/unbiased-teacher

Paper: https://arxiv.org/abs/2102.09480

Project: https://ycliu93.github.io/projects/unbiasedteacher.html

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Fake News 84 Papers #Fake_News #Papers @Machine_learn

A great note to become a data engineer by Chip Huyen:

- Data formats
- ETL
- Batch processing vs Stream processing
...

https://docs.google.com/document/u/0/d/1b9iuZiDEGVLHyMmnf6w2y1aN6yWQhAyqk3GHlpI9q6M/mobilebasic


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Real-Time Hand sign Recognition using Python and TensorFlow API

Check the Article here:- https://codeperfectplus.herokuapp.com/real-time-hand-sign-recogntion-using-tesnorflow

Android app download link in the Article.

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Data-driven health estimation and lifetime prediction of lithium-ion
batteries: A review #Paper #ML @Machine_learn

100 numpy exercises
A joint effort of the numpy community
#Numpy #python
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10 Minutes to pandas
#pandas #python
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MIT Introduction to Deep Learning

And specifically, lecture about RNN and its modifications:
https://youtu.be/qjrad0V0uJE

The course is excellent as well, but more about image processing. For NLP beginners, such clear and elegant survey about RNNs will be quite useful. So, a lot of architectures in NLP models came from image processing tasks. If you want to recap some theory or get understanding of basics of DL — strong recommendation!

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Deep Reinforcement
Learning in Action #book @Machine_learn

LEAF: A Learnable Frontend for Audio Classification


http://ai.googleblog.com/2021/03/leaf-learnable-frontend-for-audio.html

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Leveraging Machine Learning for Game Development


http://ai.googleblog.com/2021/03/leveraging-machine-learning-for-game.html

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XLA: Optimizing Compiler for Machine Learning

Tensorflow: https://www.tensorflow.org/xla

XLA Architecture: https://www.tensorflow.org/xla/architecture

Github: https://github.com/tensorflow/tensorflow/tree/master/tensorflow/compiler/xla

Code: https://www.tensorflow.org/xla/tutorials/jit_compile

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سلام دوستان جهت کسب اطلاعات از نحوه خرید می تونین با بنده در ارتباط باشین
@Raminmousa

Recursive Classification: Replacing Rewards with Examples in RL


http://ai.googleblog.com/2021/03/recursive-classification-replacing.html

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Ted Talk with Yann LeCun

in which Yann discusses his current research into self-supervised machine learning, how he's trying to build machines that learn with common sense (like humans) and his hopes for the next conceptual breakthrough in AI.

▶️ Watch

@Machine_learn

PlenOctrees For Real-time Rendering of Neural Radiance Fields

And yet another speed-up of NERF. Exactly the same idea as in FastNeRF and NEX (predict spherical harmonics coefficients k) - incredible! It's the first time I see so many concurrent papers sharig the same idea. But this one has code at least, which makes it the best!

📝 Paper arxiv.org/abs/2103.14024
🌐Project page alexyu.net/plenoctrees/
🛠Code github.com/sxyu/volrend


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