Algorithms (English)

   Tuesday, September 29, 2020   

Starting a new Lecture Notes Series on Algorithms

Youtube Lecture Playlist Credits 

Channel Name: Abdul Bari

Faculty Name: Abdul Bari Sir 

So Let Us Start to This Journey of Learning Algorithms By Lecture Notes 

together!

Daily Notes Writer Profile: Protyusha Chaudhuri

Lecture Description of this above Topic:

Lecture 1: Introduction to Algorithm

Lecture 2: Priori Analysis And Posteriori Testing

Lecture 3: Characteristics Of Algorithm

Lecture 4: How to Write and Analyze Algorithm

Lecture 5: Frequency Count Method

Lecture 6: Time Complexity #1

Lecture 7: Time Complexity #2

Lecture 8: Time Complexity #3

Lecture 9: Classes of Functions

Lecture 10: Compare Class of Function

Lecture 11: Asymptotic Notations Big Oh-Omega - Theta #1

Lecture 12: Asymptotic Notations Big Oh-Omega - Theta #2

Lecture 13: Properties of Asymptotic Notations

Lecture 14: Comparison of Functions #1

Lecture 15: Comparison of Functions #2

Lecture 16: Best Worst and Average Case Analysis

Lecture 17: Disjoint Set Data Structure

Lecture 18: Divide and Conquer

Lecture 19: Recurrence Relation #1

Lecture 20: Recurrence Relation #2

Lecture 21: Recurrence Relation #3

Lecture 22: Recurrence Relation #4

Lecture 23: Masters Theorem Decreasing Function

Lecture 24: Recurrence Relation Dividing Function #1

Lecture 25: Recurrence Relation Dividing Function #2

Lecture 26: Recurrence relation #3

Lecture 27: Masters Theorem in Algorithms for Dividing Function #1

Lecture 28: Examples for Masters Theorem

Lecture 29: Root Function(Recurrence Relation)

Lecture 30: Binary Search Iterative Method

Lecture 31: Binary Search Recursive Method

Lecture 32: Heap - Heap Sort - Heapify - Priority Queues

Lecture 33: Two Way MergSort - Iterative Method

Lecture 34: Merge Sort Algorithm

Lecture 35: MergeSort in-depth Analysis

Lecture 36: QuickSort Algorithm

Lecture 37: QuickSort Analysis

Lecture 38: Strassens Matrix Multiplication

Lecture 39: Greedy Method - Introduction

Lecture 40: Knapsack Problem - Greedy Method

Lecture 41: Job Sequencing with Deadlines - Greedy Method

Lecture 42: Optimal Merge Pattern - Greedy Method

Lecture 43: Huffman Coding - Greedy Method

Lecture 44: Prims and Kruskals Algorithms - Greedy Method

Lecture 45: Dijkstra Algorithm - Sibgle Source Shortest Path - Greedy Method

Lecture 46: Principal of Optimality - Dynamic Programming Introduction

Lecture 47: MultiStage Graph - Dynamic Programming

Lecture 48: MultiStage Graph(Program) - Dynamic Programming

Lecture 49: All Pairs Shortest Path (Floyd-Warshall) - Dynamic Programming

Lecture 50: Matrix Chain Multiplication - Dynamic Programming

Lecture 51: Matrix Chain Multiplication using Dynamic Programming Formula

Lecture 52: Matrix Chain Multiplication (Program) - Dynamic Programming

Lecture 53: Bellman Ford Algorithm - Single Source Shortest Path - Dynamic Programming

Lecture 54: Knapsack - Two Methods - Dynamic Programming

Lecture 55: Knapsack Problem (Program) - Dynamic Programming

Lecture 56: Optimal Binary Search Tree (Successful Search Only) - Dynamic Programming

Lecture 57: Optimal Binary Search Tree Successful and Unsuccessful Probability - Dynamic Programming

Lecture 58: Traveling Salesman Problem - Dynamic Programming using Formula

Lecture 59: Reliability Design - Dynamic Programming

Lecture 60: Longest Common Subsequence(LCS) - Recursion Dynamic Programming

Lecture 61: Graph Traversals - BFS & DFS -Breadth First Search and Depth First Search

Lecture 62: Articulation Point and Biconnected Components

Lecture 63: Introduction to Backtracking - Brute force Approach

Lecture 64: N Queen Problem using Backtracking

Lecture 65: Sum of Subsets Problem - Backtracking

Lecture 66: Graph Coloring Problem - Backtracking

Lecture 67: Hamiltonian Cycle - Backtracking

Lecture 68: Branch and Bound Introduction

Lecture 69: Job Sequencing with Deadline - Branch and Bound

Lecture 70: Knapsack using Branch and Bound

Lecture 71: Travelling Salesman Problem - Branch and Bound

Lecture 72: NP-Hard and NP-Complete Problems

Lecture 73: NP-Hard Graph Problem - Clique Decision Problem

Lecture 74: Knuth-Morris-Pratt KMP String Matching Algorithm

Lecture 75: Rabin-Karp String Matching Algorithm

Lecture 76: AVL Tree - Insertion Rotations

Lecture 77: B Trees and B+ Trees. How they are useful in databases

Lecture 78: Asymptotic Notations

Lecture 79: Hashing Technique

Lecture 80: Shortest Path Algorithms

Lecture 81: BFS DFS

Lecture 82: Tower of Hanoi Problem

Lecture 83: Row-Mjor and Coloumn-mjaor Mapping

Lecture 84: Merge Sort Algorithm