In a nutshell, Machine Learning is a way to give computers the powers of generalization. And that's what I try to do: put [seemingly complicated] things simply. My posts on Machine Learning (ML) focus mainly on recent cutting edge research, and how to make it accessible to everyone. I felt like many academic guides weren't accessible enough, so I strove to make my guides as clear and practically-focused as possible.
Unsure where to start? Here are some of my best / most popular posts:
Similar tags include Tensorflow, GANs, and Private Machine Learning.
Enjoy!
An example that's probably closer to what you're experiencing in coding interviews
ReadA simple way to use TPUs with minimal hardware optimization
ReadAnnouncement for the work I did with the TFP Team at Google
ReadA quick guide on how to start using Attention in your NLP models
ReadGuest Post by Michael Shwe
Announcement for the work I did with the TFP Team at Google
Read