Algorithms#
Algorithms and data structures are the operator’s mental inventory: how they work, when each applies, and what each costs in time and memory. Picking the right one is the difference between a recon job that completes overnight and one that runs out the clock on the operator.
The treatment here is language-agnostic; per-language implementations live with the languages themselves.
How an algorithm’s resource use grows with input size. Big-O, time, space.
The containers underneath the algorithms. Operations fast and slow.
The most-studied algorithmic problem. By timestamp, by score, by exposure.
Find me X. Choice of algorithm depends on what’s known about the data.
Networks, dependencies, routing, scheduling, recommendations.
Search, parsers, edit distance, fuzzy matching.
Algorithm design strategies. Recognizing when a problem fits one.