ssh
to the remote instance (based on Ubuntu Deeplearning AMI) with port* redirection:
ssh -L 8888:127.0.0.1:8888 ubuntu@IP
- activate the environment (here we're using
tensorflow_p36
):
source activate tensorflow_p36
- launch
jupyter
:
ssh
to the remote instance (based on Ubuntu Deeplearning AMI) with port* redirection:ssh -L 8888:127.0.0.1:8888 ubuntu@IP
tensorflow_p36
):source activate tensorflow_p36
jupyter
:File > Open ...
New > Terminal
tar czvhf coursera.tar.gz *
split -b 500M -d coursera.tar.gz coursera.
When running snap
inside lxc
container, snap install
might fail with the following output for :
$ systemctl status snap-core-2898.mount
● snap-core-2898.mount - Mount unit for core
Loaded: loaded (/etc/systemd/system/snap-core-2898.mount; enabled; vendor preset: enabled)
Active: failed (Result: exit-code) since Tue 2017-09-26 15:36:39 UTC; 26s ago
Where: /snap/core/2898
What: /var/lib/snapd/snaps/core_2898.snap
#!/bin/bash | |
# Mohamed Saad Ibn Seddik | |
set -e # exit with nonzero exit code if anything fails | |
# go to the out directory | |
cd ${DEPLOY_DIR} || exit 1 | |
# initiate new git repo inside the new deploy folder | |
git init |
# when using the new C++11 for loops: | |
# for (auto i : range) {} | |
target_compile_features(myapp PRIVATE cxx_range_for) |
# To be copied in /etc/ld.so.con.d/ | |
# Manually installed Qt5 | |
/home/big/Qt/5.4/gcc_64/lib | |
# Do not forget to run ldconfig after to update the cache! |
#!/bin/bah | |
mount -o loop -t iso9660 file.iso /mnt/test |
#!/bin/bash | |
export CMAKE_PREFIX_PATH=$CMAKE_PREFIX_PATH:$HOME/Qt/5.4/gcc_64 |
#!/bin/bash | |
#this script looks for a window named Mozilla Firefox and then starts procedure to select all mails in the current folder and archive them | |
for i in {1..30} | |
do | |
xdotool search --name "Mozilla Firefox" key s+a | |
xdotool search --name "Mozilla Firefox" key e | |
sleep 5 | |
done |
## Add freshly installed libraries | |
export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/usr/local/lib |