Here I’ll outline the broad concept areas that interest me and drill down where appropriate into more detail.

Data Science

This collection of pages introduces core data science concepts that interest me, and includes discussion of why I am interested in them:

  • Supervised learning is a basic machine learning technique that uses examples of input-output mappings to learn a function that takes a new, possibly unobserved, input and estimates its output label (categorical or numeric).

  • Reinforcement learning is a more advanced machine learning technique that uses the theory of Markov Decision Processes and the Bellman equations which solve them to learn to approximate an optimal policy of action from an observed reward signal.

  • Causal ML (external link) combines machine learning with the robust but relatively new field of Causal inference. My primary encounters with causal inference so far have been through Richard McElreath’s Statistical Rethinking course, but I am intrigued by the possibilities of incorporating causal theory with automated machine learning systems.

Water Quality

This collection of pages introduces core water quality concepts that interest me (pages may not yet exist).

The Nexus

There are a lot of concepts that interest me, so perhaps the most effective way of summarizing my interests (primarily for myself, as I don’t really expect anyone else to read this) is by first defining their common attributes or nexus.

Rapid list:

  • environmental processes
  • environmental systems modeling
  • environmental protection
  • environmental statistics
  • environmental infrastructure and operations
  • operations research
  • decision theory
  • complex systems analysis
  • game theory
  • probabilistic programming
  • evoloutionary and genetic programming
  • neural information processing (deep learning)
  • Bayesian statistics
  • reinforcement learning

ML Engineering/MLOps

In this section I’ll collect the best resources I find in my efforts to understand the objectives and requirements of MLOps, and begin to outline my own take on the subject as it intersects with the more traditional model development and management lifecycle of water-quality and environmental infrastructure modeling.

Go to section

Towards Intelligent Environmental Infrastructure

This should just be a blog topic?