Home Courses Interview Preparation Course Factorial: Time and Space complexity

Factorial: Time and Space complexity

Instructor: admin Duration: 21 mins



@20:20 the space complexity of mergesort call stack space complexity log(n)

Prev
Next
Substitution method.
Recursion vs iteration

16 Comment(s)

Login to comment
1.1
Why study DS and Algorithms?

20 min
2.1
Recursion tree method

15 min
2.2
Master theorem

21 min
2.3
Extended Master Theorem

9 min
2.4
Inadmissible cases & Shortcuts

6 min
2.5
Substitution method.

15 min
4.1
Solved Problem 1
4 min
4.2
Fibonacci: Time Complexity
7 min
4.3
Solved Problem 2
6 min
4.4
Solved Problem 3
7 min
4.5
Solved Problem 4 + Master Theorem Shortcut
6 min
4.6
Solved Problem 5
3 min
4.7
Solved Problem 6
4 min
4.8
Solved Problem 7
5 min
4.9
Solved Problem 8
8 min
4.10
Solved Problem 9
8 min
4.11
Solved Problem 10
7 min
5.1
Linear Search: intuition and code
10 min
6.1
Intuition
19 min
6.2
Pseudo code
9 min
7.1
Introduction: Fibonacci numbers
34 min
7.2
Longest Common Subsequence (LCS)

33 min
7.3
LCS: Example
21 min
7.4
0/1 Knapsack
31 min
7.5
0/1 Knapsack: example
21 min
7.6
Matrix Chain Multiplication
36 min
7.7
Subset-sum problem
23 min
7.8
Traveling Salesman problem
20 min
7.9
Bellman Ford Algorithm as Dynamic Programming
18 min
7.10
Floyd Warshall Algorithm as Dynamic Programming
12 min
7.11
Multi Stage Graph
30 min
8.1
Greedy Algorithms: Fractional Knapsack
30 min
8.2
Solved Problem 1
10 min
8.3
Huffman Coding for Data Compression
31 min
8.4
Solved Problem 2
7 min
8.5
Solved Problem 3
4 min
8.6
Solved Problem 4
4 min
8.7
Job Sequencing with deadlines
16 min
8.8
Solved Problem 5
5 min
8.9
Optimal Merge Pattern
14 min
8.10
Solved Problem 6
5 min
8.11
Solved Problem 7
4 min
8.12
Minimum Spanning Trees: Prim's algorithm
20 min
8.13
Minimum Spanning Trees: Greedy Kruskal's Algorithm
15 min
8.14
Greedy Algorithm: Dijkstra's algorithm
16 min