  This open-source book represents our attempt to make deep learning
approachable, teaching readers the concepts, the context, and the code. The
entire book is drafted in Jupyter notebooks, seamlessly integrating exposition
figures, math, and interactive examples with self-contained code. Our goal is
to offer a resource that could (i) be freely available for everyone; (ii) offer
sufficient technical depth to provide a starting point on the path to actually
becoming an applied machine learning scientist; (iii) include runnable code,
showing readers how to solve problems in practice; (iv) allow for rapid
updates, both by us and also by the community at large; (v) be complemented by
a forum for interactive discussion of technical details and to answer
questions.
