I visualize ANOVA results with Raincloud plots. Here’s a great paper (with #Rstats code) on this visualization approach from @micahgallen + team https://t.co/m2OF4bstXW pic.twitter.com/rjc4ZsahhL
— Dan Quintana (@dsquintana) April 14, 2020
I visualize ANOVA results with Raincloud plots. Here’s a great paper (with #Rstats code) on this visualization approach from @micahgallen + team https://t.co/m2OF4bstXW pic.twitter.com/rjc4ZsahhL
— Dan Quintana (@dsquintana) April 14, 2020
The highest quality Jupyter notebook I've ever seen was just posted by... <checks notes>... ex-CEO of Instagram, Kevin Systrom?
— Chris Said (@Chris_Said) April 13, 2020
All of us data scientists can hang our heads in shame.
h/t (@seanjtaylor )https://t.co/LU1PSHNveW
The coronavirus is likely to hit poorer countries particularly hard, but it is also laying a bigger burden on working class people even in wealthy ones. Source: https://t.co/8GUmH46uqo pic.twitter.com/TrDv3h5hax
— Simon Kuestenmacher (@simongerman600) April 13, 2020
This map shows the global manufacturing output. I'd expect that post-corona many countries will try to strengthen their local manufacturing sector so they don't rely on a foreign power for essentials. Source: https://t.co/wcpcurE5Tb pic.twitter.com/BNw1LzKHyU
— Simon Kuestenmacher (@simongerman600) April 13, 2020
Wow, I've never succeeded to explain the concept of gghighlight this well... Thanks so much @allison_horst!!!👍👍👍 https://t.co/ounv6K0X5f
— Hiroaki Yutani (@yutannihilat_en) April 11, 2020
Karl Friston is using Dynamic Causal Modeling to understand #COVIDー19 https://t.co/2ePRlCI92S pic.twitter.com/guwjmEk6C6
— danilobzdok (@danilobzdok) April 10, 2020
This was a really cool integration to work on.
— Julien Chaumond (@julien_c) April 9, 2020
If you have a model you'd like to visualize in ExBERT, let us know and we'll let you know how to add it.
hat/tip @Ben_Hoov @hen_str @sebgehr for the ExBERT repohttps://t.co/k2Gphl6YZp
This Youtube channel by @giswqs is a great resource for example usages of @ProjectJupyter's #ipyleaflet. Check it out! https://t.co/TIzwMI9gKu
— Sylvain Corlay (@SylvainCorlay) April 9, 2020
The 2nd wave of #COVID19 modeled from the China's 1st-wave data @TheLancet Premature relaxing of mitigation will increase the transmissibility (Ri); this requires real-time monitoringhttps://t.co/p4vJ6CZA56
— Eric Topol (@EricTopol) April 8, 2020
by @gmleunghku @hkumed w/ Kathy Leung, Joseph Wu pic.twitter.com/UqCZvCNPHV
Data proves just how good Breaking Bad was. Source: https://t.co/RnPcO8zm4d pic.twitter.com/kRcY2vLYUG
— Simon Kuestenmacher (@simongerman600) April 8, 2020
The frequency of random seeds between 0 and 1000 on github (data from https://t.co/xwutMzNI2N) pic.twitter.com/Zmp7mwMWil
— Jake VanderPlas (@jakevdp) April 8, 2020
UMAP 0.4 is now out! It includes a host of new features, including plotting support, better sparse data support, inverse transforms, and embedding to non-euclidean manifolds.
— Leland McInnes (@leland_mcinnes) April 7, 2020
pip install umap-learn
See this thread for some of the new features: https://t.co/pscMWXg6xG