Deep Learning Course

Deep Learning Course is an open-source course on deep learning topics hosted on GitHub in the Machine Learning Mindset repository built with the guidance of our client, Amirsina Torfi. We have designed and created four modules -- introduction, basic, neural network, and deep neural network concepts -- with each module containing subtopics. This course will introduce users to some key concepts used in developing and using deep learning and neural network models.

The approach to constructing this course was to split our time between researching, developing in-depth documentation on topics, and developing source code to go along with some of the topics. Users may navigate through the course, module by module and subtopic by subtopic in a linear fashion within each module, and execute the supplied sample code. In addition to providing documentation on the topics within deep learning, we supply information on various PyTorch and Python libraries used in the source code. This is to provide supplementary information on the specifics of the code. The goal is to have the user gain a further understanding of deep learning and its application in PyTorch and Python.

Our course addresses the problems of lack of resources and limited availability of open-source courses on deep learning. Our solution includes contextual materials in addition to source code. The main component of our project is the GitHub repository, with reStructuredText documentation. The repository is publicly available for viewing and suggestions. Thus our group provided the desired open-source course deliverable. To use our course, visit https://github.com/machinelearningmindset/deep-learning-course