Data Science by ODS.ai ๐Ÿฆœ
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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: @malev
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โ€‹โ€‹Important article in Nature about statistical significance

Scientists rise up against statistical significance โ€” about motion to move from widely using and quoting statistical significance to confindence intervals.

Link: https://www.nature.com/articles/d41586-019-00857-9

#statistics #statsignificance #nature #science
Ranking Items With Star Ratings and How Not To Sort By Average Rating

Two absolute must read articles for proper sorting handling. Sorting items with just an average score is wrong and there is some good classic statistics explanation why.

Link: https://www.evanmiller.org/ranking-items-with-star-ratings.html
Link2: https://www.evanmiller.org/how-not-to-sort-by-average-rating.html

#Statistics #rating #scoring #ranking
๐Ÿ“šGuest post on great example of book abandonment at GoodReads

An excellent new article from Gwern on analyzing abandoned (hard to finish, hard to read) books on Goodreads. This write up includes step by step instructions with source code, even the way he parsed the data from the website without an API.

Itโ€™s a shame analysis like this does not come from an online book subscription service like Bookmate or MyBook. They have vastly superior datasets and many able data scientists. I am quite sure amazon kindle team does prepare internal reports like that for some evil business purposes, but thatโ€™s a whole different story.

During my time at video game database company RAWG.io weโ€™ve compiled โ€˜most abandonedโ€™ and โ€˜most addictiveโ€™ reports for video games.

Do you make a popular service with valuable user behavior data? Funny data analysis reports are a good way to get some attention to your product. Take a lead from Pornhub, they are great at publicizing their data.

Link: https://www.gwern.net/GoodReads
Pornhub Insights: https://www.pornhub.com/insights/

โ€”
This is a guest post by Samat Galimov, who writes about technology, programming and management in Russian on @ctodaily.


#DataAnalysis #GoodReads #statistics #greatstats #talkingnumbers
Benfordโ€™s Law, DS and the 2020 Election

This law can be used for the very basic check on wether the data was artificially generated or not. It assumes that lower digits have higher probability of occuring.

And there can be nothing better for #reproducibleresearch concept promotion, than #openresearch on poll data, because it shows that those can and should be transparent and open.

With the help of the repo below anyone can check compliance of poll data results with the #BenfordsLaw on unofficial (or official if you are able to get that data).

KDnuggets tutorial: https://www.kdnuggets.com/2020/09/diy-election-fraud-analysis-benfords-law.html
Github repo with examples on unofficial US election data: https://github.com/cjph8914/2020_benfords

#statistics
๐Ÿ”ฅEverything You Always Wanted To Know About GitHub (But Were Afraid To Ask)

ClickHouse team provided extensive statistics on GitHub, including but not limited to distribution of repositories by star count, top repositories by stars, affinity list, top labels etc.

All the data is available for download with instructions for ClickHouse import

Link: https://gh.clickhouse.tech/explorer/

#GitHub #ClickHouse #Yandex #statistics #EDA #engineerketing
๐Ÿฆœ 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 โ€” post about deep neural networks (> 1 layer)
#cv โ€” posts related to Computer Vision. Pictures and videos
#nlp #nlu โ€” Natural Language Processing and Natural Language Understanding. Texts and sequences
#audiolearning #speechrecognition โ€” related to audio information processing
#ar โ€” augmeneted reality related content
#rl โ€” Reinforcement Learning (agents, bots and neural networks capable of playing games)
#gan #generation #generatinveart #neuralart โ€” about neural artt and image generation
#transformer #vqgan #vae #bert #clip #StyleGAN2 #Unet #resnet #keras #Pytorch #GPT3 #GPT2 โ€” related to special architectures or frameworks
#coding #CS โ€” content related to software engineering sphere
#OpenAI #microsoft #Github #DeepMind #Yandex #Google #Facebook #huggingface โ€” hashtags related to certain companies
#productionml #sota #recommendation #embeddings #selfdriving #dataset #opensource #analytics #statistics #attention #machine #translation #visualization


Chats

- Data Science Chat https://yangx.top/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
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