Machine Learning (ML) Notes  [large file; opens in new tab]
Implementation Notes here.


In 2014 as I was reviewing and implementing various natural language processing (NLP) platforms, I was noting the advent of machine learning (ML) in the NLP / BioNLP domain. At that time, the leading BioNLP platforms performed reasonably well BioNLP Shared Task challenges; however, I often found these systems to be heavily engineered: too often unwieldy and buggy.

Conversely, (ML) approaches to NLP were rapidly advancing, demonstrating remarkable performance with minimal engineering. Looking for new solutions, I started following that literature, rather thoroughly immersing myself in that domain from the Fall of 2014 to present. Along the way, I implemented much code (some of which is described in my Personal Projects page).

Needless to say, I am much-enamoured by the myriad applications of ML / artificial intelligence. That period of study provided me great insight into the numerous applications of ML in my own work.

While the time I’m devoting to that domain is abating somewhat as I refocus on my Vision, I am posting my notes – that pretty accurately summarize the breadth and scope of the ML literature, projects, innovations and applications that I deemed worthy of noting and saving.

You may find that content Machine Learning (ML) Notes  « [large file; opens in new tab]. Over the coming weeks and months I will point out / highlight some of the particularly interesting content.

I hope that you find it as fascinating, as well. Enjoy!