Design and Analysis of algorithms (DAA)
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Gate Smashers (79 videos)
Tracks in this Playlist
L-1.1: Introduction to Algorithm & Syllabus Discussion for GATE/NET & Placements Preparation | DAA
L-1.2: What is Algorithm | How to Analyze an Algorithm | Priori vs Posteriori Analysis | DAA
L-1.3: Asymptotic Notations | Big O | Big Omega | Theta Notations | Most Imp Topic Of Algorithm
L-1.4: Various Properties of Asymptotic Notation with Example | Algorithm | DAA
L-1.5: Comparison of Various Time Complexities | Different types in Increasing Order| Must Watch
L-1.6: Time Complexities of all Searching and Sorting Algorithms in 10 minute | GATE & other Exams
L-1.7: Question#1 on Comparison of Various Time Complexities | GATE Questions
L-1.8: Question#2 on Comparison of Various Time Complexities | GATE Questions
L-2.1: What is Recurrence Relation| How to Write Binary Search Recurrence Relation|How we Solve them
L-2.2: Recurrence Relation [ T(n)= T(n/2) + c] | Substitution Method | Algorithm
L-2.3: Recurrence Relation [ T(n)= n*T(n-1) ] | Substitution Method | Algorithm
L-2.4: Recurrence Relation [ T(n)= 2T(n/2) +n] | Substitution Method | Algorithm
L-2.5: Recurrence Relation [ T(n)= T(n-1) +logn] | Substitution Method | Algorithm
L-2.6: Recurrence Relation [ T(n)= 8T(n/2) + n^2 ] | Master Theorem | Example#1 | Algorithm
L-2.7: Recurrence Relation [ T(n)= T(n/2) +c] | Master Theorem | Example-2 | Algorithm
L-2.8: Recurrence Relation T(n)=T(√n)+logn | Master Theorem
L-2.9: Recurrence Relation [T(n)= 2T(n/2) +cn] | Recursive Tree method | Algorithm
L-2.10: Recurrence Relation [T(n)= 3T(n/4) +cn^2] | Recursive Tree method | Algorithm
L-3.0: Divide and Conquer | Algorithm
L-3.1: How Quick Sort Works | Performance of Quick Sort with Example | Divide and Conquer
L-3.2: Performance of Quick Sort | Worst Case Time Complexity with Example | Algorithm
L-3.3: How Merge Sort Works?? Full explanation with example
L -3.4: Merge Sort Pseudocode | Merge Sort with example
L-3.5: Imp. Question on Merge Sort | Divide and Conquer | Algorithm
L-3.6: How Bubble Sort Works | Performance of Bubble Sort | All Imp Points with Example | Algorithm
L-3.7: Insertion Sort | Time Complexity Analysis | Stable Sort | Inplace Sorting
L-3.8: Selection Sort | Time Complexity(Best, Avg & Worst) Analysis | Stable or Not | Inplace or Not
L-3.9: Radix Sort | Easiest explanation with example
L-3.10: Counting Sort | Easiest explanation with example
L-3.11: Bucket Sort | Easiest explanation with examples | Time Complexity analysis with Pseudocode
L-3.12: Introduction to Trees (Binary Tree, Almost Complete Binary Tree, Full BT, Complete BT, BST)
L-3.13: Introduction to Heap Tree with examples | Max Min Heap
L-3.14: Insertion in Heap Tree | Max-Heap & Min-Heap Creation | Time Complexities
L-3.15: Imp Question on Max Heap | GATE Question on Max/Min Heap | Algorithm
L-3.16: Build Heap in O(n) time complexity | Heapify Method | Full Derivation with example
L-3.17: Deletion in Heap tree | Time complexity
L-3.18: Heap sort with Example | Heapify Method
L-4.1: Introduction to Greedy Techniques With Example | What is Greedy Techniques
L-4.2: Knapsack Problem With Example| Greedy Techniques| Algorithm
L-4.3: Huffman Coding Algorithm in Hindi with Example | Greedy Techniques(Algorithm)
L-4.4: Huffman Coding Question in Greedy Technique | Imp Question for all competitive exams
L-4.5: Job Sequencing Algorithm with Example | Greedy Techniques
L-4.6: Optimal Merge Pattern using Greedy Method in Hindi | Algorithm
L-4.7: What is Spanning Tree with Examples in Hindi | Algorithm
L-4.8: Kruskal Algorithm for Minimum Spanning Tree in Hindi | Algorithm
L-4.9: Prim's Algorithm for Minimum Cost Spanning Tree | Prims vs Kruskal
L-4.10: Dijkstra's Algorithm - Single Source Shortest Path - Greedy Method
L-4.11: Dijkstra's Algorithm Analysis | Time Complexity | Pseudocode Explanation
L-4.12: Why does Dijkstra fail on Negative Weights?? Full Explanation with examples
L-4.13: Bellman Ford Algorithm | Dijkstra's Vs Bellman Ford | Single Source Shortest Path
L-4.14: Bellman Ford pseudo code and Time complexity | Single Source Shortest Path
L-4.15: BFS & DFS | Breadth First Search | Depth First Search | Graph Traversing | DAA
L-5.1: Introduction to Dynamic Programming | Greedy Vs Dynamic Programming | Algorithm(DAA)
L-5.2: 0/1 Knapsack failed using Greedy approach
L-5.3: 0/1 Knapsack Problem |Dynamic Programming |Recursive Equation |Recursion Tree Time Complexity
L-5.4: Traveling Salesman Problem | Dynamic Programming
L-5.5: Sum of Subsets Problem | Dynamic Programming
L-5.6: Multistage Graph | Dynamic Programming
L-5.7: Introduction to All Pair Shortest Path (Floyd Warshall Algorithm)
L-5.8: Floyd Warshall Working with example | All Pair Shortest Path Algorithm
L-5.9: Floyd Warshall Time & Space complexity | All Pair Shortest Path
L-6.1: What is hashing with example | Hashing in data structure
L-6.2: Collision Resolution Techniques in Hashing | What are the collision resolution techniques?
L-6.3: Chaining in Hashing | What is chaining in hashing with examples
L-6.4: Linear Probing in Hashing with example
L-6.5: Imp Question on Hashing | Linear Probing for Collision in Hash Table | GATE Questions
L-6.6: Quadratic Probing in Hashing with example
L-6.7: Double Hashing | Collision Resolution Technique
L- 6.8:Topological Sorting with examples | Topological Sorting using DFS
L-6.9:Kahn's Algorithm | Topological Sorting | DAA | Imp for Placements
Lec-41: Branch & Bound Algorithm with Example | Easiest Explanation of B&B with example
Lec-42 : 0/1 Knapsack using Branch and Bound with example
Shortcut for Swaps🔁 in Bubble🫧 Sorting📶| Best Case | Worst Case
Optimized Bubble Sort | Best Case | O(n) Time Complexity | Sorting Algorithms |DAA
Recurrence Relation [T(n) = 2T(n/2) + 2] | Min-Max Algorithm
Min-Max Algorithm without Divide & Conquer🏆 | Linear Approach | Find Max & Min
Min Max Algorithm with Divide & Conquer🏆
Time complexity and Comparison of All Data Structures
Bubble Sort Pseudocode | Performance & Time Complexity