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Check out my Dynamic Programming course (founders edition available): ...

Design Analysis of Algorithm Knapsack Problem Using Greedy Programming. Step by step explained inn this video.

Greedy algorithms explained step by step: what a greedy algorithm is (make the best choice now and never go back), coin change ...

Full course — free exercises, summary notes, and AI-graded feedback: https://ludium.ai/courses/data-science-python Every ...

Full course — free exercises, summary notes, and AI-graded feedback: https://ludium.ai/courses/data-science-python Brute force ...

Your airline cabin bag has a hard 7 kg limit (or your phone has only 7 GB free). You have items with weights and a usefulness ...

Dynamic programming explained with simple patterns: why naive recursive Fibonacci makes millions of calls, overlapping ...

Python dynamic programming: solve each subproblem once with memoisation (functools lru_cache) or tabulation, then use it on ...

Dynamic programming explained from zero: a laptop counts the ways to climb 40 stairs and needs 27 seconds and 331 million ...

Solve the classic 0/1 Knapsack problem in Python, step by step. A thief with a 7 kg backpack can take a book (1 kg, $10), ...

LeetCode 956 Tallest Billboard is a Hard problem: up to 20 rods, whose lengths add up to at most 5000, are welded into two ...

In this video we learn two important algorithm topics with simple, visual examples. Part 1: Branch and Bound. We solve a 0/1 ...

Weekly Contest 525, Question 2 (Medium). The statement invites you to simulate k operations, and the obvious greedy (rearrange ...

Coin Change, a classic coding interview problem for top product companies, explained step by step. We see why greedy fails, ...