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First Telegram Data Science channel. Covering all technical and popular staff about anything related to Data Science: AI, Big Data, Machine Learning, Statistics, general Math and the applications of former. To reach editors contact: @opendatasciencebot

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Data Science by ODS.ai 🦜

Nature has published an article with a #superresolution approach for #CT scans.

https://www.sciencedaily.com/releases/2018/03/180321155324.htm
#arxiv: https://arxiv.org/abs/1704.08841

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Graph shows what people really mean when they use vague terminology describing the probability of an event.

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Data Science by ODS.ai 🦜

Another paper on automl: Neural Nets learning to design Neural Nets.

A reinforcement learning agent that learns to program new neural network architectures.
Same/better results as LSTMs but with funky nonlinearities (sine, SeLus, etc) and new connections that result in different activation patterns.

Arxiv: https://arxiv.org/abs/1712.07316
Post: https://einstein.ai/research/domain-specific-language-for-automated-rnn-architecture-search

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Data Science by ODS.ai 🦜

pix2pix Demo: Neural network generates cityscape based on the input label map.

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Data Science by ODS.ai 🦜

Video displaying progress of GANs for photo generation. Now you can use neural networks to generate HD photo of a person who never existed.

https://www.youtube.com/watch?v=XOxxPcy5Gr4

#GAN #youtube

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Data Science by ODS.ai 🦜

An article about the impossibility of intelligence explosion. There will be no singularity or significant breakthrough and humanity will die off becuase of sun explosion.

francois.chollet/the-impossibility-of-intelligence-explosion-5be4a9eda6ec" rel="nofollow">https://medium.com/@francois.chollet/the-impossibility-of-intelligence-explosion-5be4a9eda6ec

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Astonishing results on emotion generation and image altering with StarGAN

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Data Science by ODS.ai 🦜

#CapsNet #tutorial on the YouTube

https://www.youtube.com/watch?v=pPN8d0E3900

#deeplearning

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Data Science by ODS.ai 🦜

And another posts on #CapsNet and how they work.

Capsule Networks Are Shaking up AI — Here’s How to Use Them: https://hackernoon.com/capsule-networks-are-shaking-up-ai-heres-how-to-use-them-c233a0971952

Understanding Hinton’s Capsule Networks. Part I: Intuition:
pechyonkin/understanding-hintons-capsule-networks-part-i-intuition-b4b559d1159b" rel="nofollow">https://medium.com/@pechyonkin/understanding-hintons-capsule-networks-part-i-intuition-b4b559d1159b

Understanding Hinton’s Capsule Networks. Part II: How Capsules Work:
pechyonkin/understanding-hintons-capsule-networks-part-ii-how-capsules-work-153b6ade9f66" rel="nofollow">https://medium.com/@pechyonkin/understanding-hintons-capsule-networks-part-ii-how-capsules-work-153b6ade9f66

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Data Science by ODS.ai 🦜

On 1st of November Geoff Hinton — one of the top NN researches has published two papers introducing new approach for #CV problems: Capsule Networks.

These architecture allows to recognize a face on the picture by detecting eyes, nose, mouth, regardless of the position / scaling / rotating the elements.

In other words, these approach allows neural network to be invariant to transformation of object.


First of papers: https://arxiv.org/abs/1710.09829
Second paper: https://openreview.net/forum?id=HJWLfGWRb&noteId=HJWLfGWRb

Article on Wired: https://www.wired.com/story/googles-ai-wizard-unveils-a-new-twist-on-neural-networks/

Explanation on hackernoon: https://hackernoon.com/what-is-a-capsnet-or-capsule-network-2bfbe48769cc

Another post with explanation: https://kndrck.co/posts/capsule_networks_explained/

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Data Science by ODS.ai 🦜

Google's open source candy for all ML community:

Source-to-Source Debuggable Derivatives


https://opensource.googleblog.com/2017/11/tangent-source-to-source-debuggable.html?m=1

#opensource #nn #python #google

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Data Science by ODS.ai 🦜

The State of Data Science & Machine Learning 2017 by Kaggle.

Very informative article about age, job titles, most popular languages and everything related to DS / ML.

Not to mention that source data is included.

https://www.kaggle.com/surveys/2017

#kaggle #statistics

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Data Science by ODS.ai 🦜

Winning approaches for solving Advanced Driver Assistance System challenge on Kaggle:

https://blog.getnexar.com/how-a-22-year-old-from-shanghai-won-a-global-deep-learning-challenge-76f2299446a1

#deeplearning #kaggle #cv

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https://twitter.com/pleonard/status/914671877146206208

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NLP for beginners

http://blog.kaggle.com/2017/08/25/data-science-101-getting-started-in-nlp-tokenization-tutorial/

#tutorial #nlp

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“Listing Embeddings for Similar Listing Recommendations and Real-time Personalization in Search”

From #Airbnb team
https://medium.com/airbnb-engineering/listing-embeddings-for-similar-listing-recommendations-and-real-time-personalization-in-search-601172f7603e

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Data Science by ODS.ai 🦜

Unfortunately, discrimination against ML competition participants becomes more frequent. CrowdANALYTIX recently launched a competition that simply bans different countries from opportunity to participate, this time including Russia.

Spread the word so that we could make Data Science and ML more open, without obsolete discriminatory rules on competition platforms:
https://www.facebook.com/DataChallenges/photos/a.136318350296824.1073741827.136313013630691/182693245659334/?type=3&theater

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Data Science by ODS.ai 🦜

High-Resolution Image Synthesis and Semantic Manipulation with Conditional GANs.

Now mankind can generate content for social networks without taking photoes.

Github: https://github.com/NVIDIA/pix2pixHD
Arxiv: https://arxiv.org/pdf/1711.11585.pdf

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Data Science by ODS.ai 🦜

AI index report, demonstrating hype around AI techonologies: https://aiindex.org/2017-report.pdf

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#DeepLearning predicts when patients die with Average Precision 0.69 (that’s high).

Andrew Ng announced new project in his twitter: ML to help prioritize palliative (end-of-life) care. Model uses an 18-layer Deep Neural Network that inputs the EHR data of a patient, and outputs the probability of death in the next 3-12 months.

The trained model achieves an AUROC score of 0.93 and an Average Precision score of 0.69 on cross validation.

Site: https://stanfordmlgroup.github.io/projects/improving-palliative-care/
Arxiv: https://arxiv.org/abs/1711.06402

#project #DSinthewild #casestudy

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StarGAN — a novel and scalable approach that can perform image-to-image translations for multiple domains using only a single model.

GitHub: https://github.com/yunjey/StarGAN
Arxiv: https://arxiv.org/abs/1711.09020

#deeplearning #gan #cv

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Data Science by ODS.ai 🦜

Realtime object detection by Google.

https://research.googleblog.com/2017/11/automl-for-large-scale-image.html

YouTube demo: https://www.youtube.com/watch?time_continue=70&v=ERglPgx8wFg

#deeplearning #google #caption #detection

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An article about #BigBrother. How Facebook is able to track users interests based on 3 likes.

Enhancing Transparency and Control When Drawing Data-Driven Inferences About Individuals

http://online.liebertpub.com/doi/full/10.1089/big.2017.0074

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#CapsNet #architecture

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Data Science by ODS.ai 🦜

Imitation learning for structured prediction in natural language processing

https://sheffieldnlp.github.io/ImitationLearningTutorialEACL2017

#nlp #tutorial

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Data Science by ODS.ai 🦜

Release of a nice NLP-processing library.

https://www.techleer.com/articles/404-spacy-20-released-natural-language-processing-with-python/

#nlp #python

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Data Science by ODS.ai 🦜

Great example of feature visualisation

https://distill.pub/2017/feature-visualization/

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Data Science by ODS.ai 🦜

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

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Data Science by ODS.ai 🦜

Another breakthrough with generative models.

BEGAN: Boundary Equilibrium Generative Adversarial Networks

https://arxiv.org/abs/1703.10717

#gan #cv

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Data Science by ODS.ai 🦜

Netflix shared its recommendation engine scheme:

https://medium.com/netflix-techblog/distributed-time-travel-for-feature-generation-389cccdd3907

#ml #rs #spark #hadoop

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