Deep Learning Resources for Beginners (Updated Mid 2018 - Outdated!)

This is a curated list of resources for picking up deep learning for business. Please understand that this is not an exhaustive list by any means or even a complete list of what I have. It's also what I found helpful - so it is biased. If you have any suggestions, please contact me. Basic knowledge of ML is assumed. If not, please take this classic Andrew Ng's Coursera class. 

Suggested Usage

1. Take Andrew Ng's Classic ML course and understand everything (skip if you know classic ML). I highly recommend reference books such as Elements of Statistical Learning and Pattern Recognition and Machine Learning. Both books are EXCELLENT and FREE. 
2. Go over item number 5 for foundation of neural networks - I find this to be the most clear and easy tutorial. I learned NN from my favorite ML book Chris Bishop book (the other is Elements of Statistical Learning)  in my undergrad class but I think I would've liked item number 5 better as an intro for NN. 
3. Go browse all the entries among the blogs to get high level overview of different DL models and get the topology of the DL space
4. read(1)  if want("deepdive") else read(2) or take(12 or https://course.fast.ai/)
5. Pick up and learn (tensorflow+keras/mxnet/pytorch/etc) and implement your models. Start by going over examples online! Google + Stackoverflow for all :)
6. Brainstorm research questions and write papers! Good luck! :)

This is a work in progress.