A collection of Jupyter notebooks for various ML tasks.
If you're having trouble viewing the notebooks in GitHub, try using nbviewer.
Create the virtual environment with the following commands:
$ mkdir -p ~/dev
$ python -m venv ~/dev/.venv
$ source ~/dev/.venv/Scripts/activate
$ echo "Confirm you're using the correct python with: "
$ which python
=> Should show path to your .venvAlternatively, you can use the provided bash scripts to enter into it with source-ry.
$ ./create-venv.sh
$ source source-me-to-activate-venv.sh(.venv)
$ pip install -e ".[dev]"In the above, ".[dev]" means you want to install the optional packages under 'dev' in the project pyproject.toml.
There is also a visual mode driven by networkx and matplotlib. To install dev tools plus visual mode, use this pip install command instead:
(.venv)
$ pip install -e ".[dev,jupyter]"See this reference for more info about installing Python packages.
Now you can run the application from within the virtual environment:
(.venv)
$ aiwRun tests:
(.venv)
$ python -m pytest -v tests/See the docs directory for more.
Once installed, the application can be run via the command line. Inside your virtual environment:
(.venv)
$ aiw --help
usage: aiw [-h] [-c CONFIG] [-v] [-w WARN] {anneal,svm,convolve} ...
options:
-h, --help show this help message and exit
-c CONFIG, --config CONFIG
config file [etc/config.toml]
-v, --version print version and exit
-w WARN, --warn WARN logger warning level [WARN]
subcommands:
{anneal,svm,convolve}
(.venv-ai)The application uses TOML files for configuration. Configuration supports
runtime parameter substitution via a shell-like variable syntax, i.e.
var = ${VALUE}. CLI invocation will use the current environment for
parameter substitution, which makes it simple to pass host-specific values
to the application without needing to change the config file for every
installation. Config file is located in /etc.
logging = "INFO"The application uses standard Python logging. All logging is to STDERR,
and the logging level can be set via the config file or on the command line.
Find the code in the core module.