Deep Learning Resources for Beginners (Updated Mid 2018 - Outdated!)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
This is a work in progress.
Suggested Usage
- 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.
- 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.
- 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
- read(1) if want("deepdive") else read(2) or take(12 or https://course.fast.ai/)
- Pick up and learn (tensorflow+keras/mxnet/pytorch/etc) and implement your models. Start by going over examples online! Google + Stackoverflow for all :)
- Brainstorm research questions and write papers! Good luck! :)
This is a work in progress.