[New] Matrix Chain Multiplication using Dynamic Programming Formula
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[New] Matrix Chain Multiplication using Dynamic Programming Formula
52:02
4.6.2 [New] Optimal Binary Search Tree Successful and Unsuccessful Probability - Dynamic Programming
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4.6.2 [New] Optimal Binary Search Tree Successful and Unsuccessful Probability - Dynamic Programming
57:00
Bresenham's Line Drawing Algorithm
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Bresenham's Line Drawing Algorithm
43:39
2.6.3 Heap - Heap Sort - Heapify - Priority Queues
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2.6.3 Heap - Heap Sort - Heapify - Priority Queues
51:08
4.9 Longest Common Subsequence (LCS) - Recursion and Dynamic Programming
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4.9 Longest Common Subsequence (LCS) - Recursion and Dynamic Programming
23:35
7.3 Traveling Salesman Problem - Branch and Bound
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7.3 Traveling Salesman Problem - Branch and Bound
24:42
DDA Line Drawing Algorithm - Computer Graphics
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DDA Line Drawing Algorithm - Computer Graphics
26:48
4.8 Reliability Design - Dynamic Programming
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4.8 Reliability Design - Dynamic Programming
26:32
8.1 NP-Hard Graph Problem - Clique Decision Problem
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8.1 NP-Hard Graph Problem - Clique Decision Problem
17:14
6.4 Hamiltonian Cycle - Backtracking
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6.4 Hamiltonian Cycle - Backtracking
18:35
1.12 Disjoint Sets Data Structure - Weighted Union and Collapsing Find
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1.12 Disjoint Sets Data Structure - Weighted Union and Collapsing Find
26:04
4.7 [New] Traveling Salesman Problem - Dynamic Programming using Formula
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4.7 [New] Traveling Salesman Problem - Dynamic Programming using Formula
17:18
6. Everything about Variables in JAVA
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6. Everything about Variables in JAVA
29:05
9.2 Rabin-Karp String Matching Algorithm
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9.2 Rabin-Karp String Matching Algorithm
23:50
10.2 B Trees and B+ Trees. How they are useful in Databases
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10.2 B Trees and B+ Trees. How they are useful in Databases
39:41
5. Everything about JAVA Data Types
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5. Everything about JAVA Data Types
27:54
4. Why public static void main(String args[ ]) ? JAVA
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4. Why public static void main(String args[ ]) ? JAVA
13:18
3. Why to Set Path ? JAVA
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3. Why to Set Path ? JAVA
14:02
9.1 Knuth-Morris-Pratt KMP String Matching Algorithm
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9.1 Knuth-Morris-Pratt KMP String Matching Algorithm
18:56
2. Why and How Java is platform independent
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2. Why and How Java is platform independent
19:04
1. Why One should Learn Java - Introduction to Java
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1. Why One should Learn Java - Introduction to Java
14:27
10.1 AVL Tree - Insertion and Rotations
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10.1 AVL Tree - Insertion and Rotations
43:08
4.3.1 Matrix Chain Multiplication (Program) - Dynamic Programming
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4.3.1 Matrix Chain Multiplication (Program) - Dynamic Programming
18:40
4.5.1 0/1 Knapsack Problem (Program) - Dynamic Programming
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4.5.1 0/1 Knapsack Problem (Program) - Dynamic Programming
17:00
1.1 Priori Analysis and Posteriori Testing
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1.1 Priori Analysis and Posteriori Testing
1:48
4.1.1 MultiStage Graph (Program) - Dynamic Programming
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4.1.1 MultiStage Graph (Program) - Dynamic Programming
14:26
8. NP-Hard and NP-Complete Problems
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8. NP-Hard and NP-Complete Problems
31:53
7.2 0/1 Knapsack using Branch and Bound
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7.2 0/1 Knapsack using Branch and Bound
10:48
7.1 Job Sequencing with Deadline - Branch and Bound
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7.1 Job Sequencing with Deadline - Branch and Bound
10:56
6.3 Graph Coloring Problem - Backtracking
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6.3 Graph Coloring Problem - Backtracking
15:52
7 Branch and Bound Introduction
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7 Branch and Bound Introduction
9:40
6.2 Sum Of Subsets Problem - Backtracking
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6.2 Sum Of Subsets Problem - Backtracking
12:19
6.1 N Queens Problem using Backtracking
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6.1 N Queens Problem using Backtracking
13:41
6 Introduction to Backtracking - Brute Force Approach
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6 Introduction to Backtracking - Brute Force Approach
8:15
5.2 Articulation Point and Biconnected Components
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5.2 Articulation Point and Biconnected Components
8:37
5.1 Graph Traversals - BFS & DFS -Breadth First Search and Depth First Search
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5.1 Graph Traversals - BFS & DFS -Breadth First Search and Depth First Search
18:31
Abdul Bari Live Stream
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Abdul Bari Live Stream
4.6 Optimal Binary Search Tree (Successful Search Only) - Dynamic Programming
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4.6 Optimal Binary Search Tree (Successful Search Only) - Dynamic Programming
30:19
4.7 Traveling Salesperson Problem - Dynamic Programming
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4.7 Traveling Salesperson Problem - Dynamic Programming
15:25
4.5 0/1 Knapsack - Two Methods - Dynamic Programming
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4.5 0/1 Knapsack - Two Methods - Dynamic Programming
28:24
4.4 Bellman Ford Algorithm - Single Source Shortest Path - Dynamic Programming
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4.4 Bellman Ford Algorithm - Single Source Shortest Path - Dynamic Programming
17:12
4.3 Matrix Chain Multiplication - Dynamic Programming
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4.3 Matrix Chain Multiplication - Dynamic Programming
23:00
4.1 MultiStage Graph - Dynamic Programming
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4.1 MultiStage Graph - Dynamic Programming
21:07
4.2 All Pairs Shortest Path (Floyd-Warshall) - Dynamic Programming
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4.2 All Pairs Shortest Path (Floyd-Warshall) - Dynamic Programming
14:13
4 Principle of Optimality - Dynamic Programming introduction
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4 Principle of Optimality - Dynamic Programming introduction
14:52
3.6 Dijkstra Algorithm - Single Source Shortest Path - Greedy Method
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3.6 Dijkstra Algorithm - Single Source Shortest Path - Greedy Method
18:35
3.5 Prims and Kruskals Algorithms - Greedy Method
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3.5 Prims and Kruskals Algorithms - Greedy Method
20:12
3.4 Huffman Coding - Greedy Method
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3.4 Huffman Coding - Greedy Method
17:44
3.2 Job Sequencing with Deadlines - Greedy Method
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3.2 Job Sequencing with Deadlines - Greedy Method
13:29
3.3 Optimal Merge Pattern - Greedy Method
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3.3 Optimal Merge Pattern - Greedy Method
9:33
3.1 Knapsack Problem - Greedy Method
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3.1 Knapsack Problem - Greedy Method
15:30
3. Greedy Method - Introduction
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3. Greedy Method - Introduction
12:02
2.9 Strassens Matrix Multiplication
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2.9 Strassens Matrix Multiplication
23:40
2.8.2 QuickSort Analysis
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2.8.2 QuickSort Analysis
11:37
2.8.1 QuickSort Algorithm
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2.8.1 QuickSort Algorithm
13:43
2.7.3 MergeSort in-depth Analysis
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2.7.3 MergeSort in-depth Analysis
13:28
1.5.3 Time Complexity of While and if #3
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1.5.3 Time Complexity of While and if #3
21:54
2.7.2. Merge Sort Algorithm
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2.7.2. Merge Sort Algorithm
24:07
2.7.1 Two Way MergeSort - Iterative method
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2.7.1 Two Way MergeSort - Iterative method
20:19
2.6.1 Binary Search Iterative Method
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2.6.1 Binary Search Iterative Method
19:36
2.6.2 Binary Search Recursive Method
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2.6.2 Binary Search Recursive Method
7:11
2.4.2 Examples for Master Theorem #2
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2.4.2 Examples for Master Theorem #2
5:41
2.4.1 Masters Theorem in Algorithms for Dividing Function #1
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2.4.1 Masters Theorem in Algorithms for Dividing Function #1
16:50
2.5 Root function (Recurrence Relation)
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2.5 Root function (Recurrence Relation)
5:37
2.3.3 Recurrence Relation [ T(n)= 2T(n/2) +n] #3
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2.3.3 Recurrence Relation [ T(n)= 2T(n/2) +n] #3
11:20
2.3.2 Recurrence Relation Dividing [ T(n)=T(n/2)+ n]. #2
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2.3.2 Recurrence Relation Dividing [ T(n)=T(n/2)+ n]. #2
7:26
2.3.1 Recurrence Relation Dividing Function T(n)=T(n/2)+1 #1
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2.3.1 Recurrence Relation Dividing Function T(n)=T(n/2)+1 #1
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2.2 Masters Theorem Decreasing Function
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2.2 Masters Theorem Decreasing Function
8:10
2.1.4 Recurrence Relation T(n)=2 T(n-1)+1 #4
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2.1.4 Recurrence Relation T(n)=2 T(n-1)+1 #4
10:42
2.1.3 Recurrence Relation (T(n)= T(n-1) + log n) #3
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2.1.3 Recurrence Relation (T(n)= T(n-1) + log n) #3
12:25
2.1.2 Recurrence Relation (T(n)= T(n-1) + n) #2
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2.1.2 Recurrence Relation (T(n)= T(n-1) + n) #2
16:00
2.1.1 Recurrence Relation (T(n)= T(n-1) + 1) #1
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2.1.1 Recurrence Relation (T(n)= T(n-1) + 1) #1
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2 Divide And Conquer
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2 Divide And Conquer
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1.11 Best Worst and Average Case Analysis
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1.11 Best Worst and Average Case Analysis
18:56
1.10.2 Comparison of Functions #2
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1.10.2 Comparison of Functions #2
10:26
1.10.1 Comparison of Functions #1
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1.10.1 Comparison of Functions #1
9:28
1.9 Properties of Asymptotic Notations
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1.9 Properties of Asymptotic Notations
11:58
1.8.2 Asymptotic Notations - Big Oh - Omega - Theta #2
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1.8.2 Asymptotic Notations - Big Oh - Omega - Theta #2
10:07
1.8.1 Asymptotic Notations Big Oh - Omega - Theta #1
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1.8.1 Asymptotic Notations Big Oh - Omega - Theta #1
15:46
1.7 Compare Class of Functions
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1.7 Compare Class of Functions
5:11
1.6 Classes of functions
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1.6 Classes of functions
3:10
1.5.2 Time Complexity Example #2
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1.5.2 Time Complexity Example #2
14:13
1.5.1 Time Complexity #1
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1.5.1 Time Complexity #1
10:08
1.4 Frequency Count Method
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1.4 Frequency Count Method
12:22
1.3 How Write and Analyze Algorithm
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1.3 How Write and Analyze Algorithm
10:37
1.2 Characteristics of Algorithm
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1.2 Characteristics of Algorithm
5:37
1. Introduction to Algorithms
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1. Introduction to Algorithms
11:49
Why Object Orientation - Hindi
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Why Object Orientation - Hindi
25:07
Java AWT Listeners Coding Styles #7
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Java AWT Listeners Coding Styles #7
17:35
Java AWT Coding Styles #6
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Java AWT Coding Styles #6
8:00
Java AWT Event Listeners #5
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Java AWT Event Listeners #5
6:03
Java AWT Event Classes #4
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Java AWT Event Classes #4
11:06
Java AWT Event Handling #3
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Java AWT Event Handling #3
8:48
Java AWT Simple App #2
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Java AWT Simple App #2
8:54
Java AWT - #1
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Java AWT - #1
20:30
How Java is Platform Independent
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How Java is Platform Independent
10:23
Shortest Path Algorithms (Dijkstra and Bellman-Ford) - Simplified
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Shortest Path Algorithms (Dijkstra and Bellman-Ford) - Simplified
26:13
Websites vs WebApps
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Websites vs WebApps
15:09
BFS DFS - Simplified
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BFS DFS - Simplified
19:13
Asymptotic Notations - Simplified
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Asymptotic Notations - Simplified
22:44