@Machine_learn

​​In a chord diagram (or radial network), entities are arranged radially as segments with their relationships visualised by arcs that connect them. The size of the segments illustrates the numerical proportions, whilst the size of the arc illustrates the significance of the relationships1.

Chord diagrams are useful when trying to convey relationships between different entities, and they can be beautiful and eye-catching.

https://github.com/shahinrostami/chord

#python

@Machine_learn

The TensorFlow tutorials are written as Jupyter notebooks and run directly in Google Colab—a hosted notebook environment that requires no setup.

FROM BEGINNERS TO EXPERTS
* Source Codes
* Videos
* Libraries and extensions

https://www.tensorflow.org/tutorials

@Machine_learn

NeRF: Neural Radiance Fields


https://www.matthewtancik.com/nerf

Tensorflow implementation: https://github.com/bmild/nerf

Paper: https://arxiv.org/abs/2003.08934v1

Python Artificial Intelligence Projects for Beginners
#python #book #AI
@Machine_learn

Training with quantization noise for extreme model compression

@Machine_learn

https://ai.facebook.com/blog/training-with-quantization-noise-for-extreme-model-compression/

Paper: https://arxiv.org/abs/2004.07320

GitHub: https://github.com/pytorch/fairseq/tree/master/examples/quant_noise

Reinforcement Learning and Optimal Control
by #book #RL

@Machine_learn

Adversarial Latent Autoencoders (ALAE) not only generate 1024x1024 images with StyleGAN’s quality but also allow to manipulate real-world images in a feed-forward manner. Your move, StyleGAN team!
paper: arxiv.org/abs/2004.04467
code: github.com/podgorskiy/ALAE
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Deep Learning for NLP and Speech Recognition (2019)
#Book #NLP #Speech_Recognition
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@Machine_learn

TFRT: A new TensorFlow runtime

https://blog.tensorflow.org/2020/04/tfrt-new-tensorflow-runtime.html

@Machine_learn


Combinatorial 3D Shape Generation
via Sequential Assembly

https://arxiv.org/pdf/2004.07414.pdf
https://arxiv.org/abs/2004.07414

@Machine_learn

Reinforcement Learning with Augmented Data

https://mishalaskin.github.io/rad

Code: https://github.com/MishaLaskin/rad

Paper: https://arxiv.org/abs/2004.14990

@Machine_learn

BASNet was already great for salient object detection and background removal.

Repo: https://github.com/NathanUA/U-2-Net

Watsapp: +989333900804
ID: @Machine_learn

deep learning in computer vision
#book #DL
@Machine_learn

@Machine_learn
Global explanations for discovering bias in data

Github: https://github.com/agamiko/gebi

Code: https://github.com/AgaMiko/GEBI/blob/master/notebooks/GEBI.ipynb

Paper: https://arxiv.org/abs/2005.02269v1

Machine Learning A Bayesian and Optimization Perspective
#book #ML
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