Algorithms to live by and why should we care
summary
Covers concrete algorithms, when they actually help and what numbers matter: binary search halves the search space each guess, the 37% rule for optimal stopping, recursion with base cases, and concrete sorts from bubble to quicksort with tradeoffs in effort versus lookup cost. Shows k nearest neighbors for recommendations using distance math, sketches scheduling heuristics like shortest processing time, and ends with a real-world failure where an airline’s optimization de-prioritises a passenger, arguing for transparency and attention to who an algorithm harms.
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chapters (17)
- 0:00Intro
- 0:40What are algorithms
- 3:28Why should we care
- 7:11Optimal stopping
- 9:01Optimal solution
- 10:20Recursion
- 12:39Sorting
- 15:56Getting things done
- 17:01Explicit goals
- 17:38Different strategies
- 18:23Shortest processing time
- 20:11Graphs
- 25:36Charles Darwin
- 26:44Overfitting
- 27:29Strategies
- 28:56United Airlines
- 29:51Conclusion
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