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 .venv
Alternatively, 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)
$ aiw
Run 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.