Deep Dive into Algorithms

Deep Dive into Algorithms
Deep Dive into Algorithms
English | MP4 | AVC 1280×720 | AAC 44KHz 2ch | 32.5 Hours | 11.5 GB

Deep Dive into Algorithms

An algorithmic paradigm or algorithm design paradigm is a generic model or framework which underlies the design of a class of algorithms. An algorithmic paradigm is an abstraction higher than the notion of an algorithm, just as an algorithm is an abstraction higher than a computer program.

  • How does one calculate the running time of an algorithm?
  • How can we compare two different algorithms?
  • How do we know if an algorithm is ‘optimal’?

What you’ll learn

  • Students will learn various Backtracking Problems along with implementation using C language
  • Students will learn various Dynamic Programming Problems along with implementation using C language
  • Students will learn various Graph Algorithms along with implementation using C language
  • Branch and Bound
  • Divide and Conquer
  • Greedy Algorithm
  • Pattern Matching
  • Searching and Sorting
Table of Contents

Backtracking
1 Introduction
2 Concept of N Queen Problem
3 Implementation of N Queen Problem
4 Time Complexity Analysis of N Queen Problem
5 Concept of Knight’s Tour Problem
6 Implementation of Knight’s Tour Problem
7 Time Complexity Analysis of Knight’s Tour Problem
8 Concept Explanation of Rat in a Maze Problem
9 Implementation of Rat in a Maze
10 Time Complexity Analysis of Rat in a Maze
11 Concept Explanation of Subset Sum
12 Implementation of Subset Sum Problem
13 Time and Space Complexity Analysis of Subset Sum Problem
14 Concept Explanation of M-Coloring Problem
15 Implementation of M Coloring Problem
16 Time and Space Complexity Analysis of M Coloring Problem
17 Concept Explanation of Hamiltonian Cycle Problem
18 Implementation of Hamiltonian Cycle
19 Time and Space Complexity Analysis of Hamiltonian Cycle
20 Concept Explanation of Sudoku Solver
21 Implementation of Sudoku Solver
22 Time and Space Complexity Analysis of Sudoku Solver
23 Sieve of Eratosthene
24 Implementation of Sieve of Eratosthene
25 Concept Explanation of Sieve of Sundaram
26 Implementation of Sieve of Sundaram
27 Time and Space Complexity Analysis of Sieve of Eratosthene and Sieve of Sundaram
28 Sieve of Eratosthene in O(N) Time Complexity
29 Implementation of Sieve of Eratosthene in O(N) Time Complexity
30 Prime Numbers after P with Sum S
31 Implementation of Prime Numbers after P with Sum S
32 Time and Space Complexity Analysis of Prime Numbers after P with Sum S

Dynamic Programming
33 Introduction to Dynamic Programming – Part 1
34 Introduction to Dynamic Programming – Part 2
35 Kanpsack Problem
36 Implementation of 01 Knapsack Problem
37 Printing items in 01 Knapsack Problem
38 Implementation of printing items in 01 Knapsack Problem
39 Minimum Cost Path
40 Implementation of Minimum Cost Path
41 Tracing the path of Minimum Cost Path
42 Implementation of Tracing the Path of Minimum Cost Path
43 Subset Sum Problem
44 Implementation of Subset Sum Problem
45 Printing items in Subset Sum Problem
46 Implementation of printing items in Subset Sum
47 Maximum Size Square Sub Matrix with all 1s
48 Implementation of Maximum Size Square Sub Matrix with all 1s
49 Longest Increasing Subsequence
50 Implementation of Longest Increasing Subsequence
51 Printing items in Longest Increasing Subsequence
52 Implementation of Printing items in Longest Increasing Subsequence
53 Longest Common Subsequence
54 Implementation of Longest Common Subsequence
55 Tracing the String in Longest Common Subsequence
56 Implementation of Tracing the String in Longest Common Subsequence

Range Query Algorithms
57 Introduction and Brute Force Approach of Range Minimum Query
58 Implementation of Range Minimum Query ( Brute Force Approach )
59 Dynamic Programming Approach for Range Minimum Query
60 Implementation of Range Minimum Query ( Dynamic Programming Approach )
61 Introduction to Segment Tree
62 Constructing Segment Tree
63 Implementation of Constructing Segment Tree
64 Range Minimum Query on the Constructed Segment Tree
65 Implementation of Range Minimum Query on Constructed Segment Tree
66 Range Minimum Query Using Sparse Table
67 Performing RMQ on Constructed Sparse Table
68 How to efficiently fill Sparse Table
69 Implementation of RMQ using Sparse Table

Graph Algorithms
70 How to represent a adjacency list for an directed and undirected graph
71 Implementation of Adjacency List for Directed and Undirected Graph
72 HierHolzer’s Algorithm
73 Implementation of HierHolzer’s Algorithm
74 Union Find Algorithm
75 Implementation of Union Find Algorithm
76 Topological Sorting
77 Dijkstra’s Algorithm
78 Bellman Ford Algorithm
79 Ford Fulkerson Method Edmond Karg Maximum Flow Algorithm
80 Kargers Algorithm for Minimum Cut
81 Kruskal’s Algorithm for Minimum Spanning Tree
82 Prim’s Algorithm for Minimum Spanning Tree