Sliding Window Technique - Algorithmic Mental Models
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In this video, we'll begin our series of algorithmic mental models and cover the idea behind the sliding window technique. This technique allows us to reduce a typical n^2 algorithm to a linear time algorithm with minimal effort. This exploits linear time optimizations on data structures that deal with iteration and group sequential pieces of data together.
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Timestamps
00:00 Welcome
8:25 Maximum sum of contiguous subarray of size 3.
16:35 Question variants
24:50 Dynamic variant. Smallest subarray with given sum.
27:45 Smallest subarray code start
32:48 Smallest subarray solution
33:20 Longest substring with length k distinct characters
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