Fun with Algorithms
summary
Shows that binary search cuts a million-item search to ~20 steps and a 10 million search to 29, and applies it to a banana problem with up to 10,000 piles and 1,000,000,000 bananas to turn a brute force 10,000×1,000,000,000 loop into about 10,000×29 checks. Demonstrates concrete gains from using sets/dictionaries for O(1) lookups, adjacency lists, heaps, tries, and graph routines like DFS/BFS, union‑find, Dijkstra/A and Bellman‑Ford, and reduces exponential Fibonacci or subset brute force to linear or polynomial time via memoization* and sliding‑window or two‑pointer tricks.
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chapters (15)
- 0:00Introduction
- 0:45Fun with Algorithms
- 3:03Binary Search
- 7:31Bananas
- 9:17Binary searches
- 10:38Big O notation
- 13:45Data structures
- 15:45Graphs
- 18:46Trees
- 21:49Depth First Search
- 29:40Dynamic Programming
- 36:25Sliding Windows
- 38:48Happy Patrons
- 44:43How I think about algorithms
- 49:11What can you do from here
