Beyond Self-Supervision: A Simple Yet Effective Network Distillation Alternative to Improve Backbones

Github: https://github.com/PaddlePaddle/PaddleClas

Paper: https://arxiv.org/abs/2103.05959v1

👉 @bigdata_1

Введение в Машинное Обучение и Data Science

Введение в методики Машинного Обучения и Data Science
Разведочный Анализ Данных (Exploratory Data Analysis, EDA)
Категориальные признаки (разведочный анализ данных)
Разделение Данных и Метрики
Необходимая Теория (Часть 1)
Необходимая Теория (Часть 2)
Полный Пайплайн (Pipeline)
Простая Линейная Регрессия
Множественная Линейная Регрессия
Логистическая Регрессия

Полный курс на youtube

👉 @bigdata_1

Deepmind's Generally capable agents emerge from open-ended play

Blog : https://deepmind.com/blog/article/generally-capable-agents-emerge-from-open-ended-play

Paper: https://deepmind.com/research/publications/open-ended-learning-leads-to-generally-capable-agents

DeepMind Research: https://github.com/deepmind/deepmind-research

Video: https://www.youtube.com/watch?v=lTmL7jwFfdw&ab_channel=DeepMind

👉 @bigdata_1

TimeSformer: A new architecture for video understanding

https://ai.facebook.com/blog/timesformer-a-new-architecture-for-video-understanding/

Paper: https://arxiv.org/abs/2102.05095

👉 @bigdata_1

Droidlet: modular, heterogenous, multi-modal agents

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

Paper: https://arxiv.org/abs/2101.10384

Article: https://yangx.top/machinelearning_ru/279

👉 @bigdata_1

ReDet: A Rotation-equivariant Detector for Aerial Object Detection

Github: https://github.com/csuhan/ReDet

Paper: https://arxiv.org/abs/2103.07733v1

👉 @bigdata_1

Pretrained Language Model

AutoTinyBERT: Automatic Hyper-parameter Optimization for Efficient Pre-trained Language Models

Github: https://github.com/huawei-noah/Pretrained-Language-Model

Paper: https://arxiv.org/abs/2107.13686v1

AutoTinyBERT: https://github.com/huawei-noah/Pretrained-Language-Model/tree/master/AutoTinyBERT

👉 @bigdata_1

Contactless Sleep Sensing in Nest Hub

http://ai.googleblog.com/2021/03/contactless-sleep-sensing-in-nest-hub.html

👉 @bigdata_1

StyleGAN-NADA: CLIP-Guided Domain Adaptation of Image Generators

Github: https://github.com/rinongal/StyleGAN-nada

Paper: https://arxiv.org/abs/2108.00946v1

Project: https://stylegan-nada.github.io/

Dataset: https://paperswithcode.com/dataset/lsun

👉 @bigdata_1

Natural Language Processing Pipelines, Explained

https://www.kdnuggets.com/2021/03/natural-language-processing-pipelines-explained.html

👉 @bigdata_1

Google представил нейросеть для детекции туберкулеза на радиограммах

https://pubs.rsna.org/doi/10.1148/radiol.212213

👉 @bigdata_1

🥑 DALL·E Mini

Generate images from a text prompt

Demo: https://huggingface.co/spaces/flax-community/dalle-mini

Github: https://github.com/borisdayma/dalle-mini

Paper: https://wandb.ai/dalle-mini/dalle-mini/reports/DALL-E-mini--Vmlldzo4NjIxODA

👉 @bigdata_1

UPANets: Learning from the Universal Pixel Attention Networks Edit social preview

Github: https://github.com/hanktseng131415go/UPANets

Paper: https://arxiv.org/pdf/2103.08640.pdf

👉 @bigdata_1

Toward Spatially Unbiased Generative Models

Github: https://github.com/jychoi118/toward_spatial_unbiased

Paper: https://arxiv.org/abs/2108.01285v1

👉 @bigdata_1

Training GANs with Stronger Augmentations via Contrastive Discriminator Edit social preview

Github: https://github.com/jh-jeong/ContraD

Paper: https://arxiv.org/abs/2103.09742


👉 @bigdata_1

▶️ Deepminds's Perceiver: General Perception with Iterative Attention

General architecture that works on many kinds of data

https://deepmind.com/blog/article/building-architectures-that-can-handle-the-worlds-data

Github: https://github.com/deepmind/deepmind-research/tree/master/perceiver

Colab: https://colab.research.google.com/github/deepmind/deepmind_research/blob/master/perceiver/colabs/masked_language_modelling.ipynb

Paper: https://arxiv.org/abs/2103.03206

👉 @bigdata_1

You Only Look One-level Feature

Github: https://github.com/megvii-model/YOLOF

Object detector without FPN: https://github.com/chensnathan/YOLOF

Paper: https://arxiv.org/abs/2103.09460v1

👉 @bigdata_1

📸 Physics-based Noise Modeling for Extreme Low-light Photography

Github: https://github.com/Vandermode/ELD

Paper: https://arxiv.org/abs/2108.02158v1

Dataset: https://drive.google.com/drive/folders/1CT2Ny9W9ArdSQaHNxC5hGwav9lZHoqJa?usp=sharing

👉 @bigdata_1

A Gentle Introduction to XGBoost Loss Functions

https://machinelearningmastery.com/xgboost-loss-functions/

👉 @bigdata_1

Improving Contrastive Learning by Visualizing Feature Transformation

Github: https://github.com/DTennant/CL-Visualizing-Feature-Transformation

Paper: https://arxiv.org/abs/2108.02982

👉 @bigdata_1

Transformer Meets Tracker: Exploiting Temporal Context for Robust Visual Tracking

Github: https://github.com/594422814/TransformerTrack

Paper: https://arxiv.org/abs/2103.11681v1

👉 @bigdata_1