Deep Learning – The Straight Dope
This report contains an incremental sequence of notebooks designed to teach deep learning, Apache MXNet (incubating), and the gluon interface. Their goal is to leverage the strengths of Jupyter notebooks to present prose, graphics, equations, and code together in one place. If thet are successful, the result will be a resource that could be simultaneously a book, course material, a prop for live tutorials, and a resource for plagiarising (with their blessing) useful code. To their knowledge there’s no source out there that teaches either (1) the full breadth of concepts in modern deep learning or (2) interleaves an engaging textbook with runnable code. They will find out by the end of this venture whether or not that void exists for a good reason. Another unique aspect of this book is its authorship process. They are developing this resource fully in the public view and are making it available for free in its entirety. While the book has a few primary authors to set the tone and shape the content, they welcome contributions from the community and hope to coauthor chapters and entire sections with experts and community members. Already they have received contributions spanning typo corrections through full working examples. This will be added to Artificial Intelligence Resources Subject Tracer™. This will be added to Business Intelligence Resources Subject Tracer™. This will be added to Entrepreneurial Resources Subject Tracer™. This will be added to the tools section of Research Resources Subject Tracer™. This will be added to Start Up Resources for the Entrepreneur 2018 white paper.