Andrew Ng has often stated that the best approach (that he has seen) to mastering DL is to start reading papers and then to implement them.<p>But the question remains where to start.<p>Now my goal is to curate a list of papers and their difficulty to implement them so that anyone can have a roadmap of papers to learn deep learning.<p>If you want to help, please rank the papers you think are worth implementing in the following categories:
[Beginner]
[Intermediate]
[Advanced]
[Pro]
Good lists:
<a href="https://github.com/songrotek/Deep-Learning-Papers-Reading-Roadmap" rel="nofollow">https://github.com/songrotek/Deep-Learning-Papers-Reading-Ro...</a> and
<a href="https://github.com/priyaank/deep-learning" rel="nofollow">https://github.com/priyaank/deep-learning</a>