dc.contributor.author	Hopkins, James	en
dc.contributor.author	Sherman, Brendan	en
dc.contributor.author	Smith, Zachery	en
dc.contributor.author	Wynn, Eric	en
dc.date.accessioned	2019-06-25T18:35:49Z	en
dc.date.available	2019-06-25T18:35:49Z	en
dc.date.issued	2019-05-12	en
dc.description.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.	en
dc.description.notes	Python4MLFinalReport.pdf is a PDF version of our group's final report. Python4MLFinalReport.docx is an editable version of our group's final report. Python4MLFinalPresentation.pdf is a PDF version of our group's final presentation. Python4MLFinalPresentation.pptx is an editable version of our group's final presentation. Python4MLVTURCSPoster.pdf is a PDF version of our group's poster from VTURCS. machine-learning-course.pdf is a PDF version of our course as of release.	en
dc.identifier.uri	http://hdl.handle.net/10919/90655	en
dc.language.iso	en_US	en
dc.publisher	Virginia Tech	en
dc.rights	Creative Commons Attribution 3.0 United States	en
dc.rights.uri	http://creativecommons.org/licenses/by/3.0/us/	en
dc.subject	Machine learning	en
dc.subject	Python	en
dc.subject	open source	en
dc.subject	education	en
dc.title	Python4ML: An open-source course for everyone	en
dc.type	Presentation	en
dc.type	Report	en

Python4ML: An open-source course for everyone

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