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Hot data science related posts every hour. Chat: https://telegram.me/r_channels Contacts: @lgyanf
A shaded relief map of South America rendered from 3d data and satellite imagery [OC]
/r/dataisbeautiful
https://redd.it/z9onek
Share your Spotify Wrapped 2022 stats (For Everyone)
https://docs.google.com/forms/d/e/1FAIpQLScsQAJbq2xAy2zidG4YH2dejL6i7cp5khdGRojxP848tvLpNg/viewform?usp=sf_link
/r/SampleSize
https://redd.it/z916o6
Types of butter and how they’re used
/r/Infographics
https://redd.it/z8y047
[R] Overinterpretation reveals image classification model pathologies - e.g. prominent models classify a black image w/ 4-5 gray pixels as "airplane" with >99% confidence
https://arxiv.org/abs/2003.08907
/r/MachineLearning
https://redd.it/z9ec6q
Sunrise and sunset times over London for the next 6 weeks (earliest sunset and latest sunrise are about 3 weeks apart) [OC]
/r/dataisbeautiful
https://redd.it/z8nypy
What's the deal with the Data Scientist job market? (and software development in general)
I work as a software engineer, and my brother works as a data scientist, and neither of us can land a single interview. We were talking about the job market during Thanksgiving last week and we both can't seem to get any interviews after hundreds of applications. Always auto rejected by the ATS systems/HR. Every job we apply for, same story. Within 1-2 weeks, we always receive an auto rejection email. We both looked at each other's resume's and our resume's clearly list our extensive experience and it's not a resume issue. I have a Master's Degree in CS and my brother has a PhD in CS. I work as a Staff Software Engineer and my brother works as a Principal Data Scientist and we can't get interviews. It makes no sense. I have worked in software development for nearly 10 years, and my brother a data scientist for over 6 years. We are both still employed but looking for a change. And the kicker: My brother has published research on Convolutional Neural Networks for medical device applications and went to CalTech (a very top tier school on the scale of MIT/Harvard if you don't live in the US) for his Master's/PhD and he can't even get an interview. Is there a mass hiring freeze going on across the industry? What's the deal? We both feel like we are sending our resumes into the abyss and they aren't even getting seen.
/r/datascience
https://redd.it/z8sxzi
Despite the total size , the green areas of North Africa are near the size of Norway
/r/MapPorn
https://redd.it/z8v2r5
Largest Ancestry by U.S. State
/r/MapPorn
https://redd.it/z8zten
[OC] Ryanair is known for its absurdly cheap fares, and charging extra for everything else. Here is their revenue breakdown
/r/dataisbeautiful
https://redd.it/z8mt96
The United States of Sitcoms
/r/MapPorn
https://redd.it/z8mbtx
Power generation by source in EU countries (2000–2018)
/r/visualization
https://redd.it/z8oubt
"The Stack: 3 TB of permissively licensed source code", Kocetkov et al 2022 (esp Python)
https://arxiv.org/abs/2211.15533
/r/datasets
https://redd.it/z88rts
[OC] 2016 vs 2020 US Presidential Election Vote Shift Percentage
/r/dataisbeautiful
https://redd.it/z87m5s
What do you all do while you’re fitting models?
Have been running a GridSearch for the past 5 hours now, making my laptop unusable and I’ve already cleaned my entire apartment. Just wondering what y’all do while waiting? (Obviously, this doesn’t apply if you’re running models on a company server or something)
/r/datascience
https://redd.it/z8bwy0
Race Vs Homicide rate Vs Poverty Rate
/r/MapPorn
https://redd.it/z9j370
Have you ever worked on a team where another engineer/scientist isn’t productive and seems to be knowledgeable, but when implementing they have no idea.
Hi, I was wondering if anyone has experience with co workers who kind of just pretend they know what they’re doing, and skate by. I currently work with someone who hasn’t written a single line of code and keeps doing “research work” for future work. When we do team coding sessions they seem clueless. Go on mute and don’t contribute. It’s kind of impressive how long they’ve been skating by. Just wondering if this is common in the industry.
/r/datascience
https://redd.it/z9bug6
Looking for face experiession - video - dataset
Hi, I am looking for faces dataset, more specifically non speaking faces with expressions in video format.
I found hume.ai but they are not responding. Is there any website that offers/sells dataset of this kind that you could recommend?
Thanks!
/r/datasets
https://redd.it/z8nh6l
The municipalities of Qatar
/r/MapPorn
https://redd.it/z97gsy
[OC] HDI vs Fertility Rate of countries over the years 1990 to 2020.
/r/dataisbeautiful
https://redd.it/z9edgc
Q Using Bayesian Statistics to find best campaign offer at individual customer level...is Bayes Factor the best way to go?
Hello, I'm new to Bayesian Statistics and I wanted to see if any of you had suggestions for how to proceed here.
Let's say each month we offer customers one of two campaigns they can enroll in (they have to click Join using our app)....one is 20% off one purchase, the other is Rewards Points based total purchase. The campaign are randomized, meaning a customer may receive the 20% campaign 3-4 straight months.
I'm trying to determine which campaign is best to offer each customer. Since they have to enroll, I was going to use enroll percentage to determine the Bayes Factor.
For example, for customer 1 the results look as follows
20% off Campaign Enroll Percentage: 66%
Reward Points Campaign Enroll Percentage: 50%
For Prior Odds, I'm using 44% (which is the average enroll % for the 20% off campaign for all customers). The result is 59, which my understanding means that their is strong evidence in favor of the hypothesis that customer 1 responds to the 20% off campaign more than the Reward points campaign.
So here's my questions
1. First off, am I understanding Bayes Factor correctly and am I doing it right?
2. Is their a way to add a weight based on total number of campaign offers? For example, say for 20% off campaign the customer had a 100% enrollment, but only 2 campaign offers, while Rewards the customer enrolled in 4 out of 8 offers, it's seems reasonable to assume that as the customer gets more 20% offers, the enrollment % will drop from down from 100%. Does adding the prior odds do this already? Sorry if this isn't making sense.
3. Would it be better to calculate the probability density function for each campaign and compare or perhaps another Bayesian method?
Thank you for your help. I'm open to any/all suggestions and am not looking for you to do it for me. Just need some guidance.
/r/statistics
https://redd.it/z8v31u
People 15 and over spent 0 hours alone in 2013
/r/dataisugly
https://redd.it/z92c19
Number Of Counties That You’d have to Go Through To Go To An Ocean
/r/MapPorn
https://redd.it/z8ucft
Most visited destinations by international tourist arrivals
/r/dataisugly
https://redd.it/z7b83w
London Boroughs by Religion (2021 Census)
/r/MapPorn
https://redd.it/z8sg2r
Viking, Magyar and Arab raids in Europe, with the names (in red) the Vikings used to give the different countries
/r/MapPorn
https://redd.it/z8nu2n
Masterplan for Michael Jackson's "Peter Pan's Neverland" Park. By Landmark Entertainment (1990s)
/r/MapPorn
https://redd.it/z8ib6w
[OC] US GDP Per Capita 2022
/r/dataisbeautiful
https://redd.it/z836q1
top ten countries gaining and losing.
/r/MapPorn
https://redd.it/z7y9hp