Using particle flow to visualize a velocity field (and an interesting case)
/r/visualization
https://redd.it/z9algv
% of young adults with a university degree [OC]
/r/dataisbeautiful
https://redd.it/zbgsvs
[OC] 3d rendered map of Mauna Loa showing lava flow rates
/r/dataisbeautiful
https://redd.it/zaha51
Quadratic rational maps with a critical 2-cycle and a marked point of preperiod 2 and period 1, colored by dynamics of free critical point
/r/mathpics
https://redd.it/z38jnd
Map of corn on the cob street vendors in Mexico City.
I found this dataset. It can me exported to KML to parse and analyse. It's the crowdsourced geolocation of every corn on the cob street vendor in Mexico City.
I dare y'all to train a neural network on it!
/r/datasets
https://redd.it/zb2c1o
I find a graphs ability to compare data is hugely overrated.
/r/dataisugly
https://redd.it/zalyho
[OC] Time spent online has hit a ceiling, though varies widely by country
/r/visualization
https://redd.it/zap1mw
[OC] The US and Saudi Arabia TOPS ticket sales (other than the host country)
/r/dataisbeautiful
https://redd.it/zah2uf
R Statistical vs Deep Learning forecasting methods
​
https://preview.redd.it/c59sra8nwb3a1.png?width=1190&format=png&auto=webp&s=80b3f1a83d190ac0349ec97908aa806aaa03abc3
Machine learning progress is plagued by the conflict between competing ideas, with no shortage of failed reviews, underdelivering models, and failed investments in expensive over-engineered solutions.
We don't subscribe the Deep Learning hype for time series and present a fully reproducible experiment that shows that:
1. A simple statistical ensemble outperforms most individual deep-learning models.
2. A simple statistical ensemble is 25,000 faster and only slightly less accurate than an ensemble of deep learning models.
In other words, deep-learning ensembles outperform statistical ensembles just by 0.36 points in SMAPE. However, the DL ensemble takes more than 14 days to run and costs around USD 11,000, while the statistical ensemble takes 6 minutes to run and costs $0.5c.
For the 3,003 series of M3, these are the results.
https://preview.redd.it/89bhlcg9wb3a1.png?width=1678&format=png&auto=webp&s=e5471331b081142ba201b81ba3346a890d474c50
In conclusion: in terms of speed, costs, simplicity and interpretability, deep learning is far behind the simple statistical ensemble. In terms of accuracy, they are rather close.
You can read the full report and reproduce the experiments in this Github repo: https://github.com/Nixtla/statsforecast/tree/main/experiments/m3
/r/MachineLearning
https://redd.it/z9vbw7
The World’s Billionaire Population, by Country
/r/Infographics
https://redd.it/z9mp24
Am I a real reader if I listen to so many audiobooks? /s [OC]
/r/dataisbeautiful
https://redd.it/z9xln8
[OC] Lichess.org traffic during Football World Cup 2022 [UPDATED]
/r/dataisbeautiful
https://redd.it/zbfuq4
Every Song With Over 1 Billion Spotify Streams
/r/visualization
https://redd.it/zbb2l7
[OC] Results of 50,000 World Cup Knockout Simulations
/r/dataisbeautiful
https://redd.it/zb03xc
[OC] World Cup Group E table as the evening (1st Dec) progressed. All teams qualified for the knockout stage at one point.
/r/dataisbeautiful
https://redd.it/zank97
When did women get the right to vote in Europe? (Lover of Geography)
/r/MapPorn
https://redd.it/zak0zm
The news and countries the mainstream media overlooked this week, with map
/r/Infographics
https://redd.it/z9s50p
[OC] Birth months of FIFA World Cup players. The top three are January, February and March, possibly due to the "Relative age effect"
/r/dataisbeautiful
https://redd.it/zalnny
Weekly Entering & Transitioning - Thread 28 Nov, 2022 - 05 Dec, 2022
Welcome to this week's entering & transitioning thread! This thread is for any questions about getting started, studying, or transitioning into the data science field. Topics include:
* Learning resources (e.g. books, tutorials, videos)
* Traditional education (e.g. schools, degrees, electives)
* Alternative education (e.g. online courses, bootcamps)
* Job search questions (e.g. resumes, applying, career prospects)
* Elementary questions (e.g. where to start, what next)
While you wait for answers from the community, check out the [FAQ](https://www.reddit.com/r/datascience/wiki/frequently-asked-questions) and Resources pages on our wiki. You can also search for answers in [past weekly threads](https://www.reddit.com/r/datascience/search?q=weekly%20thread&restrict_sr=1&sort=new).
/r/datascience
https://redd.it/z6ncq2
Map of the world’s most and least racially tolerant countries [1248 x 617]
/r/MapPorn
https://redd.it/za74ta
Participate in a study about LGBTQ+ romantic relationship disclosure at work (18+ years old, work 30+ hours per week, have a romantic partner for 6+ months, not self-employed, work in person at least 1 day per week on average, work in the United States)
[https://usf.az1.qualtrics.com/jfe/form/SV\_bBZrWNcr7zeg2fY?TID=59](https://usf.az1.qualtrics.com/jfe/form/SV_bBZrWNcr7zeg2fY?TID=59)
Hello,
My name is Joseph Regina and I am a doctoral student in the Industrial-Organizational Psychology program at the University of South Florida conducting doctoral research under the supervision of Dr. Tammy Allen. I am inviting you to participate in a study that focuses on the unique work challenges of same-sex presenting romantic couples related to making your relationship status known and is intended to inform organizations of LGBTQ+ family-friendly policies.
Notably, the study is three timepoints and will take you under 30 minutes (\~15 minutes for Time 1, \~10 minutes for Time 2, and \~5 minutes for Time 3) to complete. Additionally, as a token of our appreciation, you will have the chance to opt in to receive $10 in Amazon gift cards.
You are eligible for this study if you meet the following criteria:
* You are over 18 years old
* You work at least 30 hours per week for pay
* You are currently romantically involved in a same-sex presenting romantic relationship for at least 6 months
* You are not self-employed
* You work at an in-person work-related site for at least 20% of your workweek (i.e., not remotely)
* You work for a company with more than 5 employees
* Your workplace is geographically located within the United States
You may access the survey by clicking here [here](https://usf.az1.qualtrics.com/jfe/form/SV_bBZrWNcr7zeg2fY?TID=59). Participation is voluntary and you can withdraw from the survey at any time.
If you have any questions about this study, please feel free to contact me at [usfworkrelationships@gmail.com](mailto:usfworkrelationships@gmail.com) or [jregina@usf.edu](mailto:jregina@usf.edu).
Thank you,
Joseph Regina
Study 003511
/r/SampleSize
https://redd.it/z9tsck
The Mississippi River and all of its tributaries. So much bigger than I ever knew.
/r/MapPorn
https://redd.it/z9zvxo