Small machine learning and AI projects
This repository holds a variety of smaller AI- and ML-related projects I've done, mostly as learning exercises. Each project is self-contained in its own directory.
For simplicity I use Anaconda to configure the runtime environment, which you can recreate with the environment.yml files here. If this file is present within a directory then use that to create an environment for that project, otherwise the code will work in the default environment jkbml created by environment.yml at the root of the repository.
Instructions. First make sure that git and Anaconda are installed on your computer. At the command line navigate to where you'd like to put your local copy of the repository, and type:
git clone https://github.com/jkboyce/ML.git
to download a local copy. Then create your runtime environment by navigating to the directory with the appropriate environment.yml file, and type:
conda env create -f environment.yml
Be sure to use the appropriate version of the .yml file for your platform (environments are not cross-platform). Creating the environment may take several minutes as Anaconda downloads the needed files.
Then activate the environment. On Windows you type (jkbml is the environment name; substitute a different one as appropriate):
activate jkbml
or for Linux and OSX:
source activate jkbml
At this point the environment is configured. Running the code varies by project. The ones that are .ipynb files are Jupyter notebooks; run them in the browser by first starting the Jupyter server on the command line:
jupyter-notebook
which should open a browser window. Then navigate to the .ipynb file of interest.
Please send any questions, comments, or bug reports! These are all MIT licensed so hack them up and republish as you wish.