data visualization with ggplot2
https://www.rstudio.com/wp-content/uploads/2015/03/ggplot2-cheatsheet.pdf
Aug 8, 2017
Aug 3, 2017
nohup - running program as background in linux
nohup ./workflow.sh & # running as background
output is saved to nohup.out
for terminate nohup
kill -9 PID number # you can check PID number with 'top' command
Installing tensorflow - pip upgrade
for details, check https://www.tensorflow.org/install/install_linux
if step 4 failed, try upgrade pip
if step 4 failed, try upgrade pip
(tensorflow)$ pip install --upgrade pip
then try step 4 again
Installing with virtualenv
Take the following steps to install TensorFlow with Virtualenv:
- Install pip and virtualenv by issuing one of the following commands:
- Create a virtualenv environment by issuing one of the following commands:where
targetDirectory
specifies the top of the virtualenv tree. Our instructions assume thattargetDirectory
is~/tensorflow
, but you may choose any directory. - Activate the virtualenv environment by issuing one of the following commands:The preceding source command should change your prompt to the following:
- Issue one of the following commands to install TensorFlow in the active virtualenv environment:If the preceding command succeeds, skip Step 5. If the preceding command fails, perform Step 5.
- (Optional) If Step 4 failed (typically because you invoked a pip version lower than 8.1), install TensorFlow in the active virtualenv environment by issuing a command of the following format:where
tfBinaryURL
identifies the URL of the TensorFlow Python package. The appropriate value oftfBinaryURL
depends on the operating system, Python version, and GPU support. Find the appropriate value fortfBinaryURL
for your system here. For example, if you are installing TensorFlow for Linux, Python 2.7, and CPU-only support, issue the following command to install TensorFlow in the active virtualenv environment:
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