3 ms·
Nothing beats reading papers. Check this out for a very comprehensive list of the most influential deep learning papers: https://github.com/songrotek/Deep-Learn
by backpropaganda 10y ago
Nothing beats reading papers. Check this out for a very comprehensive list of the most influential deep learning papers: https://github.com/songrotek/Deep-Learning-Papers-Reading-Roadmap https://github.com/songrotek/Deep-Learning-Papers-Reading-Ro...
- krick 10y agoThanks, I'll try that as well. But then again, this is specifically about deep learning. I'm asking more about something generic, systematic overview that would help me to know that I'm using some specific techinque because of reasons, and not because "deep learning is cool". Something that would include very basic, "manual" statistics approach as well as intro to NNs. I mean, I probably know that I need CNN when I'm presented with a picture, and sometimes I might guess that I might want to use RNN if I'm presented with a text I don't know how to parse, but when I want to predict something given a bunch of numbers and stuff, it is not all that obvious which exactly approach is likely to be "the right one" and which one is probably "because fashion".