A collection of Livebook .livemd examples with training datasets.
Training time: 0.637s
First time you run the Livebook notebook it will probably need to compile exla, which requires bazel to be installed.
On macOS Big Sur this worked:
% export BAZEL_VERSION=3.1.0
% curl -fLO "https://github.com/bazelbuild/bazel/releases/download/${BAZEL_VERSION}/$ bazel-${BAZEL_VERSION}-installer-darwin-x86_64.sh"
% chmod +x "bazel-${BAZEL_VERSION}-installer-darwin-x86_64.sh"
% ./bazel-${BAZEL_VERSION}-installer-darwin-x86_64.sh --user
$ wget https://github.com/bazelbuild/bazel/releases/download/3.4.0/bazel-3.4.0-linux-arm64
$ chmod u+x bazel-3.4.0-linux-arm64
$ ./bazel-3.4.0-linux-arm64
$ cd ~/bin
$ ln -s /home/pi/dev/bazel/bazel-3.4.0-linux-arm64 bazel
$ apt-get -y install build-essential autoconf libncurses5-dev libwxbase3.0-dev libwxgtk-webview3.0-gtk3-dev libgl1-mesa-dev libglu1-mesa-dev libpng-dev libssh-dev unixodbc-dev xsltproc fop libxml2-utils openjdk-11-jdk
Next step is to run Livebook, which requires Erlang and Elixir to be installed.
% git clone https://github.com/asdf-vm/asdf.git ~/.asdf
% . $HOME/.asdf/asdf.sh
% asdf plugin add erlang https://github.com/asdf-vm/asdf-erlang.git
% export KERL_CONFIGURE_OPTIONS="--without-javac --enable-lock-counter --with-microstate-accounting=extra"
% asdf install erlang 24.0-rc3
% asdf global erlang 24.0-rc3
% asdf plugin-add elixir https://github.com/asdf-vm/asdf-elixir.git
% asdf install elixir 1.12.0-rc.1-otp-24
% asdf global elixir 1.12.0-rc.1-otp-24
% cat ~/.zshrc
export PATH="$PATH:$HOME/bin"
. $HOME/.asdf/asdf.sh
Compile Livebook and start it:
% git clone https://github.com/elixir-nx/livebook.git
% cd livebook
% mix deps.get --only prod
% MIX_ENV=prod mix phx.server
Training time: 2.860s
% cd salary_prediction
% python3 salary_prediction.py
Training time: 12.639s
% cd salary_prediction
% jupyter notebook
Training time: 23.478s
% cd salary_prediction
% jupyter notebook --NotebookApp.allow_origin='https://colab.research.google.com' --port=8888 --NotebookApp.port_retries=0
Upload salaries.csv to your Google Drive and add this at the top of the notebook:
from google.colab import drive
drive.mount('/content/gdrive')
!cat ./gdrive/MyDrive/MachineLearning/salaries.csv
Then update the cell to read_csv from your actual path.
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