A Rising Library Beating Pandas in Performance

https://www.kdnuggets.com/2020/12/rising-library-beating-pandas-performance.html

Dataset: https://www.kaggle.com/colinmorris/reddit-usernames

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ViP-DeepLab: Learning Visual Perception with Depth-aware Video Panoptic Segmentation

Github: https://github.com/joe-siyuan-qiao/ViP-DeepLab

Dataset: http://semantic-kitti.org

Paper: https://arxiv.org/abs/2012.05258v1

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Fairscale is a PyTorch extension library for high performance and large scale training for optimizing training

Github: https://github.com/facebookresearch/fairscale

Documentation: https://fairscale.readthedocs.io/en/latest/

Tutorials: https://fairscale.readthedocs.io/en/latest/tutorials/index.html

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Real-Time High-Resolution Background Matting

https://grail.cs.washington.edu/projects/background-matting-v2/

Github: https://github.com/PeterL1n/BackgroundMattingV2

Paper: https://arxiv.org/abs/2012.07810v1

Video: https://www.youtube.com/watch?v=oMfPTeYDF9g

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RLax -useful building blocks for implementing reinforcement learning agents

Github: https://github.com/deepmind/rlax

deepmind article: https://deepmind.com/blog/article/using-jax-to-accelerate-our-research

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Multi-worker training with Keras

https://www.tensorflow.org/tutorials/distribute/multi_worker_with_keras

Code: https://github.com/tensorflow/docs/blob/master/site/en/tutorials/distribute/multi_worker_with_keras.ipynb

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Informer: Beyond Efficient Transformer for Long Sequence Time-Series Forecasting.

Github: https://github.com/zhouhaoyi/Informer2020

Paper: https://arxiv.org/abs/2012.07436v1

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Sketch-Generation-with-Drawing-Process-Guided-by-Vector-Flow-and-Grayscale

Github: https://github.com/TZYSJTU/Sketch-Generation-with-Drawing-Process-Guided-by-Vector-Flow-and-Grayscale

Paper: https://arxiv.org/abs/2012.09004

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🌐 Optimization Algorithms in Neural Networks

https://datascience-enthusiast.com/DL/Optimization_methods.html

Most used optimizers: https://www.theaidream.com/post/optimization-algorithms-in-neural-networks

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Learning Continuous Image Representation with Local Implicit Image Function.

https://yinboc.github.io/liif/

Github: https://github.com/yinboc/liif

Video: https://www.youtube.com/watch?v=6f2roieSY_8

Paper: https://arxiv.org/abs/2012.09161

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🔮 An end-to-end machine learning project with Python Pandas, Keras, Flask, Docker and Heroku

Article: https://towardsdatascience.com/an-end-to-end-machine-learning-project-with-python-pandas-keras-flask-docker-and-heroku-c987018c42c7

Habr Ru: https://habr.com/ru/company/skillfactory/blog/534078

Code: https://github.com/RyanEricLamb/rugby-score-prediction

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🎇 TensorFlow Tutorial

https://datascience-enthusiast.com/DL/Tensorflow_Tutorial.html

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YolactEdge: Real-time Instance Segmentation on the Edge

Github: https://github.com/haotian-liu/yolact_edge

Demo: https://www.youtube.com/watch?v=GBCK9SrcCLM

Paper: https://arxiv.org/abs/2012.12259

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🔥 DeiT: Data-efficient Image Transformers

Gittub: https://github.com/facebookresearch/deit

Facebook’s research: https://ai.facebook.com/blog/data-efficient-image-transformers-a-promising-new-technique-for-image-classification/

Paper: https://arxiv.org/abs/2012.12877v1

Vision Transformer: https://github.com/lucidrains/vit-pytorch

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🌐 Global Context Networks

Github: https://github.com/xvjiarui/GCNet

Paper: https://arxiv.org/abs/2012.13375v1


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Check the data science channel there you will find a lot of articles, links and advanced researches .
Join and learn hot topics of data science @opendatascience

​​Solving Mixed Integer Programs Using Neural Networks

Article on speeding up Mixed Integer Programs with ML. Mixed Integer Programs are usually NP-hard problems:

- Problems solved with linear programming
- Production planning (pipeline optimization)
- Scheduling / Dispatching

Or any problems where integers represent various decisions (including some of the graph problems).

ArXiV: https://arxiv.org/abs/2012.13349
Wikipedia on Mixed Integer Programming: https://en.wikipedia.org/wiki/Integer_programming

#NPhard #MILP #DeepMind #productionml #linearprogramming #optimizationproblem

Soft-IntroVAE: Analyzing and Improving Introspective Variational Autoencoders

Project: https://taldatech.github.io/soft-intro-vae-web/

Github: https://github.com/taldatech/soft-intro-vae-pytorch

Paper: https://arxiv.org/abs/2012.13253v1

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