Algorithms to live
summary
Explains concrete algorithms and their life-sized payoffs: binary search cuts 100 down to 7 guesses, the 37% rule for optimal stopping when hunting apartments or partners, recursion for nested searches and quicksort/merge sort tradeoffs for real lists, and scheduling heuristics like shortest processing time to minimize total wait. Shows K-nearest-neighbors for recommendations with Euclidean distance, cites the United Airlines overbooking algorithm as a social cost, and compares when to relax constraints versus insist on optimal solutions.
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chapters (11)
- 0:00Start
- 7:43or finding a significant other
- 8:14The secretary problem
- 12:29and needs a recursion case and a base case
- 18:16Strategy: earliest due date
- 18:33Strategy: Moore's algorithm
- 19:29Strategy: shortest processing time
- 24:01Travelling salesperson
- 25:14Building a recommendation system
- 28:26Thinking less
- 29:27The case against complexity
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