Learning Deep Learning with Keras

http://p.migdal.pl/2017/04/30/teaching-deep-learning.html

#keras

ARkit Sudoku solver built with CoreML

https://blog.prototypr.io/behind-the-magic-how-we-built-the-arkit-sudoku-solver-e586e5b685b0

#ar #cv #keras #coreml

It is important not only to build and train a model, but also to serve it in the production. Thus, this article might be a great starting point:

Deep learning in production with Keras, Redis, Flask, and Apache

https://www.pyimagesearch.com/2018/02/05/deep-learning-production-keras-redis-flask-apache/?utm_source=opendatascience

#dl #deeplearning #keras #production

​​Desnapify

Logical followup of #pix2pix project by Isola et al., based on on Keras implementation by Thibault de Boissiere allows to remove that kat/dog faces from #Snapchat photoes.


Github: https://github.com/ipsingh06/ml-desnapify
Mentioned #Keras repo: https://github.com/tdeboissiere/DeepLearningImplementations/tree/master/pix2pix

#DL

Great collections of Data Science learning materials

The list includes free books and online courses on range of DS-related disciplines:

Machine learning (#ML)
Deep Learning (#DL)
Reinforcement learning (#RL)
#NLP

Tutorials on #Keras, #Tensorflow, #Torch, #PyTorch, #Theano

Notable researchers, papers and even #datasets. It is a great place to start reviewing your knowledge or learning something new.

Link: https://hackmd.io/@chanderA/aiguide

#wheretostart #entrylevel #novice #studycontent #studymaterials #books #MOOC #meta

Keras Tuner

Fully-featured, scalable, easy-to-use hyperparameter tuning for Keras & beyond.

It supports RandomSearch, BayesianOptimization, and Hyperband. It can run locally or in a distributed setting. It's possible to have both multi-device single-model training (one machine training one model over 8 GPUs) and distributed search (many models in parallel) at the same time


documentation: https://keras-team.github.io/keras-tuner/
tweet: https://twitter.com/fchollet/status/1189992078991708160?s=21

#DL #keras #Tuning #BayesianOptimization

​​Tutorial on Generative Adversarial Networks (GANs) with Keras and TensorFlow

Nice tutorial with enough theory to understand what you are doing and code to get it done.

Link: https://www.pyimagesearch.com/2020/11/16/gans-with-keras-and-tensorflow/

#Keras #TensorFlow #tutorial #wheretostart #GAN

🏥Self-supervised Learning for Medical images

Due to standard imaging procedures, medical images (X-ray, CT scans, etc) are usually well aligned.
This paper gives an opportunity to utilize such an alignment to automatically connect similar pairs of images for training.

GitHub: https://github.com/fhaghighi/TransVW
ArXiV: https://arxiv.org/abs/2102.10680

#biolearning #medical #dl #pytorch #keras

​​Politicians phone distraction tracking as an art project

Enthusiast used livestream of flemish goverment sessions to track those politicians who distracted on the phones during their worktime.

Project website: https://driesdepoorter.be/theflemishscrollers/
Twitter: https://twitter.com/FlemishScroller

#keras #neuroart #politics #ml4sg

🦜 Hi!

We are the first Telegram Data Science channel.

Channel was started as a collection of notable papers, news and releases shared for the members of Open Data Science (ODS) community. Through the years of just keeping the thing going we grew to an independent online Media supporting principles of Free and Open access to the information related to Data Science.


Ultimate Posts

* Where to start learning more about Data Science. https://github.com/open-data-science/ultimate_posts/tree/master/where_to_start
* @opendatascience channel audience research. https://github.com/open-data-science/ods_channel_stats_eda


Open Data Science

ODS.ai is an international community of people anyhow related to Data Science.

Website: https://ods.ai



Hashtags

Through the years we accumulated a big collection of materials, most of them accompanied by hashtags.

#deeplearning #DL — post about deep neural networks (> 1 layer)
#cv — posts related to Computer Vision. Pictures and videos
#nlp #nlu — Natural Language Processing and Natural Language Understanding. Texts and sequences
#audiolearning #speechrecognition — related to audio information processing
#ar — augmeneted reality related content
#rl — Reinforcement Learning (agents, bots and neural networks capable of playing games)
#gan #generation #generatinveart #neuralart — about neural artt and image generation
#transformer #vqgan #vae #bert #clip #StyleGAN2 #Unet #resnet #keras #Pytorch #GPT3 #GPT2 — related to special architectures or frameworks
#coding #CS — content related to software engineering sphere
#OpenAI #microsoft #Github #DeepMind #Yandex #Google #Facebook #huggingface — hashtags related to certain companies
#productionml #sota #recommendation #embeddings #selfdriving #dataset #opensource #analytics #statistics #attention #machine #translation #visualization


Chats

- Data Science Chat https://t.me/datascience_chat
- ODS Slack through invite form at website

ODS resources

* Main website: https://ods.ai
* ODS Community Telegram Channel (in Russian): @ods_ru
* ML trainings Telegram Channel: @mltrainings
* ODS Community Twitter: https://twitter.com/ods_ai

Feedback and Contacts

You are welcome to reach administration through telegram bot: @opendatasciencebot