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!
Nominations for fields that are not being researched as much as they should be
ReadA few high-level patterns to look out for in any projects you start or join
ReadA Guide to starting from scratch, based on my own experiences (WARNING: LONG READ)
ReadDemo of Few-Shot Unsupervised Image-to-Image Translation
ReadAn increasingly necessary component of being engaged on ML Twitter
Read