I keep breaking and having to reinstall my Ubuntu setup, so I figured I'd make a little document that helps me do that faster. From a completely fresh install. First things first. Download and install Chrome. sudo apt update sudo apt upgrade sudo apt install curl sudo apt install vim sudo apt install git git config --global user.name "John Doe" git config --global user.email johndoe@example.com sudo apt install openssh-server sudo vim /etc/ssh/ssh_config #and change port sudo service ssh restart ssh-keygen -o -f ~/.ssh/id_rsa cat ~/.ssh/id_rsa.pub Paste key into https://gitlab.com/profile/keys or wherever your git host is. Nvidia driver. Do this first, if nothing else, so you can stop looking at a 640x480 screen. Install nvidia, cuda, and cudnn based on this . sudo add-apt-repository ppa:graphics-drivers/ppa sudo apt install nvidia-driver-410 sudo apt-mark hold nvidia-driver-410 sudo reboot Cuda 10 wget https://developer.nvidia.com/compute/cuda/10.0/Prod/local_installers/cuda-repo-ubuntu1804-10-0-local-10.0.130-410.48_1.0-1_amd64 sudo dpkg -i cuda-repo-ubuntu1804-10-0-local-10.0.130-410.48_1.0-1_amd64 sudo apt-key add /var/cuda-repo-10-0-local-10.0.130-410.48/7fa2af80.pub sudo apt-get update sudo apt-get install cuda sudo apt-mark hold cuda echo "export PATH=/usr/local/cuda-10.0/bin${PATH:+:${PATH}}" >> ~/.bashrc source ~/.bashrc cuDNN Go to https://developer.nvidia.com/rdp/cudnn-download and create an account if you don't already have one. It's free. Click "Download cuDNN v7.6.0 (May 20, 2019), for CUDA 10.0" Download all 3 files with 18.04 in the name. Specifically the runtime library, developer library, and code samples. cd Downloads sudo dpkg -i libcudnn7_7.6.0.64-1+cuda10.0_amd64.deb sudo dpkg -i libcudnn7-dev_7.6.0.64-1+cuda10.0_amd64.deb sudo dpkg -i libcudnn7-doc_7.6.0.64-1+cuda10.0_amd64.deb sudo apt-mark hold libcudnn7 libcudnn7-dev libcudnn7-doc Conda Install conda based on this . cd /tmp curl -O https://repo.anaconda.com/archive/Anaconda3-2019.03-Linux-x86_64.sh sha256sum Anaconda3-2019.03-Linux-x86_64.sh bash Anaconda3-2019.03-Linux-x86_64.sh source ~/.bashrc Tensorflow conda create --name tensorflow_p37 python=3.7 echo "alias p37='conda activate tensorflow_p37'" >> ~/.bashrc source ~/.bashrc p37 pip install matplotlib pip install numpy pip install pillow pip install pathlib pip install shutil pip install ipython pip install jupyter pip install six pip install tensorboard pip install datetime pip install neptune-client Then if you are running on a GPU... pip install tensorflow-gpu And if a CPU... pip install tensorflow Apps Slack Visual Studio Code TeamViewer Work in progress.

Ubuntu 18.04 Machine Learning Setup

I keep breaking and having to reinstall my Ubuntu setup, so I figured I'd make a little document that helps me do that faster.

From a completely fresh install.

Do this first, if nothing else, so you can stop looking at a 640x480 screen.
Install nvidia, cuda, and cudnn based on this.

wget https://developer.nvidia.com/compute/cuda/10.0/Prod/local_installers/cuda-repo-ubuntu1804-10-0-local-10.0.130-410.48_1.0-1_amd64
sudo dpkg -i cuda-repo-ubuntu1804-10-0-local-10.0.130-410.48_1.0-1_amd64
sudo apt-key add /var/cuda-repo-10-0-local-10.0.130-410.48/7fa2af80.pub
sudo apt-get update
sudo apt-get install cuda
sudo apt-mark hold cuda
echo "export PATH=/usr/local/cuda-10.0/bin${PATH:+:${PATH}}" >> ~/.bashrc
source ~/.bashrc

Go to https://developer.nvidia.com/rdp/cudnn-download and create an account if you don't already have one. It's free.
Click "Download cuDNN v7.6.0 (May 20, 2019), for CUDA 10.0"
Download all 3 files with 18.04 in the name. Specifically the runtime library, developer library, and code samples.
cd Downloads
sudo dpkg -i libcudnn7_7.6.0.64-1+cuda10.0_amd64.deb
sudo dpkg -i libcudnn7-dev_7.6.0.64-1+cuda10.0_amd64.deb
sudo dpkg -i libcudnn7-doc_7.6.0.64-1+cuda10.0_amd64.deb
sudo apt-mark hold libcudnn7 libcudnn7-dev libcudnn7-doc

Install conda based on this.

Then if you are running on a GPU...

And if a CPU...

Work in progress.