Titles of projects look ugly on homepage when words are too long.
Add HTML soft-hyphen to the title: Digitalization
-> Digital­ization
.
library(tidyverse) | |
func <- function(x){4.25*x*x + 20.45*x + 591.25} | |
ggplot(data.frame(x=c(1, 22)), aes(x=x)) + | |
stat_function(fun=func, size = 1.5) + | |
geom_hline(yintercept = 2980, color = "red", size = 2) + | |
scale_x_continuous(name = "Jahr", | |
breaks = c(1:22), | |
labels = c("2009", |
I found it rather difficult to set up a AWS EC2 server to use fast.ai in a jupyter notebook on it. Especially, since I use a Windows 10 computer (with permanent VPN). I therefore documented the way I used to make it happen. Most of it is just a combination of the fast.ai tutorial, AWS tutorials, and the very helpful tutorial by Baligh Mnassri (https://github.com/mnassrib).
Follow steps 1 to 5 detailed here: https://course.fast.ai/start_aws
The SSH connection is realized using PuTTY (https://www.putty.org/).
here
package: https://cran.r-project.org/web/packages/here/index.html
Challenge: Code is run in code
subfolder. here
things this is the base folder. Subsequent stuff breaks
Solution: Create empty .here file in root directory using Post-Install Script:
Environment
-> Post-Install Script
-> Edit Post-Install Script
touch .here
in a new lie at the end of the file# rtweet tries to automatically detect a token for the Twitter API | |
# This fails when you run the script from the command line with RScript | |
# If you have multiple tokens, this script also helps selecting the right token | |
# Code inspired by https://github.com/samzipper/SkeeterStream/blob/master/TestLookupUsers.R | |
# Requirements: | |
# You need to have set up a token with rtweet | |
# More info: https://rtweet.info/articles/auth.html | |
# Assumption token is stored at /home/username/ |