Python4ML: An open-source course for everyone

Abstract

Our project yielded a modular, open-source course on machine learning in Python. It was built under the advisement of our client, Amirsina Torfi. It is designed to introduce users to machine learning topics in an engaging and approachable way. The initial release version of the project includes a section for core machine learning concepts, supervised learning, unsupervised learning, and deep learning. Within each section, there are 2-5 modules focused on specific topics in machine learning, including accompanying example code for users to practice with. Users are expected to move through the course section-by-section, completing all of the modules within the section, reading the documentation, and executing the supplied sample codes. We chose this modular approach to better guide the users as far as where to start with the course. This is based on the assumption that users starting with a machine learning overview and the basics will likely be more satisfied with the education they gain than if they were to jump into a deep topic immediately. Alternatively, users can start at their own level within the course by skipping over the topics they already feel comfortable with. The two main components of the project are the course website and Github repository. The course uses reStructuredText for all of its documentation so we are able to employ Sphinx to generate a fully functioning website from our repository. Both the website and repository are publicly available for both viewing and suggesting changes. The design of the course facilitates collaboration in the open-source environment, keeping the course up to date and accurate.