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A library for streamlining machine learning experiments

Project description

# ex4ml

A toolkit for conducting machine learning experiments efficiently.

![image](https://gitlab.com/minds-mines/ex4ml/ex4ml/badges/master/pipeline.svg) ![image](https://gitlab.com/minds-mines/ex4ml/ex4ml/badges/master/coverage.svg)

## Description

The target audience of ex4ml is researchers conducting experiments in machine learning. The goal of ex4ml is to allow you to focus on the machine learning research while minimizing your worrying about designing and managing experiments.

The secondary audience of ex4ml is machine learning practitioners who want a simple way to test and compare machine learning approaches.

### Applications

ex4ml should work for experiments on the following and all combinations of them:

  • Multi-Modal / Multi-View learning
  • Multiple-Instance learning
  • Feature comparisons
  • Feature visualizations

### Development

#### Summary

Here is the summary of what you need to do. Read on for more details.

Install everything:

`bash pipenv install --dev `

Run tests:

`bash pipenv shell python setup.py test `

After you make changes make sure you run autopep8 to fix your code’s syntax and pylint to get feedback on what could be improved in your code.

`bash pipenv shell autopep8 --in-place --aggressive --aggressive *.py pylint src/ex4ml/*.py pylint test/*.py `

#### Pipenv

Use [pipenv](http://pipenv.readthedocs.io/en/latest/) to automatically manage isolated, virtual environments for Python projects.

Install/upgrade pipenv via the command line.

`bash pip install --upgrade pipenv `

To install modules or create a Pipfile from a requirements.txt file:

`bash pipenv install `

To install dev-modules:

`bash pipenv install --dev `

To install or uninstall modules respectively to or from your Python project:

`bash pipenv install module_name pipenv install dev_module_name --dev pipenv uninstall module_name `

To manually create a Pipfile.lock file from the installed versions:

`bash pipenv lock `

To load the Python virtual environment into the shell to execute commands or run a single command using the Python virtual environment use the following:

`bash pipenv shell pipenv run command_name `

Use exit to unload the Python virtual environment.

To see your project’s dependency graph:

`bash pipenv graph `

#### PyScaffold

This project has been set up using PyScaffold 3.0.3. For details and usage information on PyScaffold see <http://pyscaffold.org/>.

Use [PyScaffold](http://pyscaffold.org/en/latest/features.html) to quickly setup and manage Python projects.

### Installation

You will need [Git](https://git-scm.com) with user.name and user.email setup to get started.

`bash git config --global user.name "John Doe" git config --global user.email "john.doe@email.com" `

Install/upgrade setuptools and pyscaffold via the command line:

`bash pip install --upgrade setuptools pip install --upgrade pyscaffold `

### Testing

To execute unit tests in the tests directory, use:

`bash pipenv shell python setup.py test `

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