Knapsack,Algorithm Applying Memoization,Optimal Solution by Applying

Algorithms & Data Structures 3/3:DP,Hashing,Trie,Suffix Tree,DP,NPComplete,Hard,Coloring

Orientation

String Search:Hashing,Karp–Rabin,KMP,Boyer-Moore,Trie,Suffix Tree & Array

Intro, Learning objectives (0:30)
Hashing,Hash Table,Hash Function,Collision (8:11)
Pattern Matching,Brute Force,Karp–Rabin,KMP(Knuth-Morris-Pratt),Boyer-Moore (21:47)
Trie, Suffix Trie (2:56)
Suffix Tree, Compressed Trie (4:49)
Suffix Array,complexity and advantages,LCP Array (3:18)
Compression:Run-Length Encoding,Huffman,Lampel-Ziv-Welch,Arithmetic Coding (8:28)
Summary (6:03)

Introduction of Dynamic Programming,Fibonacci,Induction,Memoization,Binomial

Intro, Learning objectives (0:49)
Fibonacci Number and Function Call Tree (4:26)
Mathematical Induction and Pigeon Hole Principle (6:41)
Memoization and Dynamic Programming (14:04)
Binomial Coefficient,State Space Tree, Binomial Theorem,Pascal's Triangle (13:25)
Summary (3:14)

Knapsack,State Space Tree,Branch & Bound,Pruning,Best-First Search

Use Dynamic Programming:All Pairs Shortest Path,Floyd-Warshall,Traveling Salesman Problem

Intro, Learning objectives (0:44)
Longest Increasing Sequence,DP Approach Algorithm,Efficient Method Using BS (15:21)
All Pairs Shortest Path,Optimization problem,Brute-Force Approach,Floyd-Warshall (13:00)
Traveling Salesman Problem and Dynamic Programming Based Approach (11:44)
Summary (2:59)

NP-Complete:NP-Hard,SAT,Vertex Cover,Clique,Graph Coloring,Longest Path,Hamiltonian

Intro, Learning objectives (0:24)
P and NP (9:44)
NP-Complete (5:10)
NP-Complete Problem (5:18)
Summary (3:19)

Approximation Algorithm:Job Scheduling,Simulated Annealing,Graph of Search

Number Theory & Optimization,Probability,GCD,Euclid Algorithm,LCM,Modulo

Intro, Learning objectives (0:16)
Probability,Permutation,Combination (16:37)
Number Theory,Divisor,Prime Number,Composite,GCD,Euclid Algorithm,LCM,Modulo (8:35)
Mechanical Optimization,Operation of Floating Point Number (10:21)
Summary (5:40)

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