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:
Practical considerations of scaling and implementing ML in the real worldRead
A deep dive into the important 'deep' learning conceptsRead
Fundamentals of all types of machine learning, deep learning or otherwiseRead
Important mathematical prerequisites for getting into Machine Learning, Deep Learning, or any of the other spaceRead
A 4-post series that covers the subject material in a good machine learning engineer interview.View Series
Nominations for fields that are not being researched as much as they should beRead