Algorithms & Data Structures

This course is based on: Introduction to Algorithms (Eastern Economy Edition)
Last Updated: May 1, 2020


Algorithms and Data Structures are both core topics in a computer science cirriculum. Data structures have their distinct advantages and disadvantages and a firm understanding of the trade-offs allow computer/data scientists to apply them properly. Understanding various algorithms helps your problem-solving skills by providing you with better and sometimes non-intuitive ways to solve problems.


Recommended Prerequisites: Probability, Linear Algebra, Object-Oriented Programming (Coming Soon)

Chapter 1
Chapter 1.1: Role of Algorithms in Computing
What's an algorithm? - David J. Malan Views: 1.35M; Net Likes: 18.6K; Like Ratio: 97%; Length: 4m
Intro to Algorithms: Crash Course Computer Science #13 Views: 957K; Net Likes: 17K; Like Ratio: 98%; Length: 11m
Introduction to Big O Notation and Time Complexity (Data Structures & Algorithms #7) Views: 722K; Net Likes: 15.1K; Like Ratio: 98%; Length: 36m
Concepts of Algorithm, Flow Chart & C Programming Views: 1.3M; Net Likes: 9.49K; Like Ratio: 96%; Length: 33m
Chapter 1.3: Analyzing and Designing Algorithms
1. Introduction to Algorithms Views: 1.04M; Net Likes: 8.65K; Like Ratio: 98%; Length: 11m
1.3 How Write and Analyze Algorithm Views: 258K; Net Likes: 2.43K; Like Ratio: 98%; Length: 10m
1.2 Characteristics of Algorithm Views: 235K; Net Likes: 1.81K; Like Ratio: 98%; Length: 5m
Algorithm introduction | Design & Algorithms | Lec-1 | Bhanu Priya Views: 151K; Net Likes: 1.04K; Like Ratio: 95%; Length: 11m
Chapter 1.4: Asymptotic Notations
Algorithms Lecture 1 -- Introduction to asymptotic notations Views: 1.73M; Net Likes: 11.2K; Like Ratio: 96%; Length: 22m
1.8.1 Asymptotic Notations Big Oh - Omega - Theta #1 Views: 446K; Net Likes: 6.02K; Like Ratio: 98%; Length: 15m
Time complexity analysis: asymptotic notations - big oh, theta ,omega Views: 530K; Net Likes: 3.36K; Like Ratio: 96%; Length: 10m
Asymptotic Bounding 101: Big O, Big Omega, & Theta (Deeply Understanding Asymptotic Analysis) Views: 42.5K; Net Likes: 2.26K; Like Ratio: 99%; Length: 23m
Chapter 2
Chapter 2.1: Insertion Sort
3. Insertion Sort, Merge Sort Views: 533K; Net Likes: 3.23K; Like Ratio: 98%; Length: 51m
Algorithms Lecture 7 -- Insertion sort algorithm and analysis Views: 510K; Net Likes: 3.03K; Like Ratio: 97%; Length: 27m
7.4 Insertion Sort Algorithm | Data Structure Views: 181K; Net Likes: 2.96K; Like Ratio: 97%; Length: 28m
Insertion sort in 2 minutes Views: 206K; Net Likes: 2.62K; Like Ratio: 96%; Length: 2m
Chapter 2.2: Bubble Sort
Bubble Sort | GeeksforGeeks Views: 381K; Net Likes: 2.12K; Like Ratio: 97%; Length: 58Sm
Bubble sort in 2 minutes Views: 129K; Net Likes: 1.7K; Like Ratio: 97%; Length: 2m
Algorithms: Bubble Sort Views: 206K; Net Likes: 1.46K; Like Ratio: 96%; Length: 4m
Bubble Sort Views: 134K; Net Likes: 574; Like Ratio: 96%; Length: 1m
Chapter 2.3: Merge Sort
Merge sort algorithm Views: 1.68M; Net Likes: 12K; Like Ratio: 96%; Length: 18m
2.7.2. Merge Sort Algorithm Views: 487K; Net Likes: 4.93K; Like Ratio: 96%; Length: 20m
7.7 Merge Sort Algorithm | Sorting Algorithms| Merge Sort in Data structure Views: 157K; Net Likes: 2.7K; Like Ratio: 97%; Length: 35m
Merge Sort step by step walkthrough (Recursion) Views: 51K; Net Likes: 954; Like Ratio: 96%; Length: 7m
Chapter 2.4: Quicksort
Quicksort algorithm Views: 1.43M; Net Likes: 10.3K; Like Ratio: 95%; Length: 20m
Visualization of Quick sort (HD) Views: 588K; Net Likes: 9.31K; Like Ratio: 97%; Length: 3m
Quick Sort - Computerphile Views: 246K; Net Likes: 4.9K; Like Ratio: 99%; Length: 3m
7.6 Quick Sort Algorithm | Sorting Algorithm | Quick Sort Algorithm Explained Views: 267K; Net Likes: 3.72K; Like Ratio: 96%; Length: 24m
Chapter 2.5: Heapsort
4. Heaps and Heap Sort Views: 575K; Net Likes: 4K; Like Ratio: 98%; Length: 52m
Algorithms lecture 12 -- Max heapify algorithm and complete binary tree Views: 360K; Net Likes: 1.98K; Like Ratio: 96%; Length: 37m
7.9 Heap Sort | Heapify Method | Build Max Heap Algorithm Views: 111K; Net Likes: 1.45K; Like Ratio: 97%; Length: 46m
Heaps 5 HeapSort Views: 21.2K; Net Likes: 321; Like Ratio: 99%; Length: 8m
Chapter 2.6: Sorting in Linear Time
Algorithms Lecture 7 -- Insertion sort algorithm and analysis Views: 510K; Net Likes: 3.03K; Like Ratio: 97%; Length: 27m
7.3 Bubble Sort Algorithm| Data Structures Views: 156K; Net Likes: 2.76K; Like Ratio: 98%; Length: 35m
7. Counting Sort, Radix Sort, Lower Bounds for Sorting Views: 264K; Net Likes: 1.55K; Like Ratio: 97%; Length: 52m
Time Complexities of all Searching and Sorting Algorithms in 10 minute | Imp GATE and other Exams Views: 55.9K; Net Likes: 1.26K; Like Ratio: 98%; Length: 12m
Chapter 3
Chapter 3.1: Introduction to Divide and Conquer
Lec 3 | MIT 6.046J / 18.410J Introduction to Algorithms (SMA 5503), Fall 2005 Views: 161K; Net Likes: 381; Like Ratio: 95%; Length: 1H8m
Divide & Conquer (Think Like a Programmer) Views: 12.1K; Net Likes: 198; Like Ratio: 98%; Length: 15m
Divide & Conquer - Introduction Views: 392; Net Likes: 19; Like Ratio: 95%; Length: 13m
Chapter 3.2: Maximum-Subarray Problem
Max Contiguous Subarray Sum - Cubic Time To Kadane's Algorithm ("Maximum Subarray" on LeetCode) Views: 69.5K; Net Likes: 2.69K; Like Ratio: 98%; Length: 19m
LeetCode Challenge Day 3 - Max Subarray Views: 32.5K; Net Likes: 1.16K; Like Ratio: 99%; Length: 11m
Algorithms Lecture 13: Maximum Sub-array Problem using Divide-and-Conquer Views: 15.9K; Net Likes: 259; Like Ratio: 96%; Length: 18m
LeetCode Dynamic Programming (2019) Maximum Subarray Views: 3.47K; Net Likes: 67; Like Ratio: 97%; Length: 8m
Chapter 3.3: Substitution Method for Solving Recurrences
Algorithms lecture 3 -- Time analysis of recursive program Views: 650K; Net Likes: 3.78K; Like Ratio: 97%; Length: 24m
Solved Recurrence - Substitution (Plug-and-chug) Method Views: 143K; Net Likes: 2.06K; Like Ratio: 99%; Length: 9m
2.3.3 Recurrence Relation [ T(n)= 2T(n/2) +n] #3 Views: 241K; Net Likes: 2K; Like Ratio: 97%; Length: 11m
What is Substitution Method| How to Solve Recurrence Relation using Substitution Method | Algorithm Views: 17.7K; Net Likes: 312; Like Ratio: 97%; Length: 7m
Chapter 3.4: Recursion-Tree Method for Solving Recurrences
Solved Recurrence Tree Method Views: 213K; Net Likes: 2.1K; Like Ratio: 97%; Length: 6m
2.3.3 Recurrence Relation [ T(n)= 2T(n/2) +n] #3 Views: 241K; Net Likes: 2K; Like Ratio: 97%; Length: 11m
Recursion Tree Method Views: 103K; Net Likes: 1.08K; Like Ratio: 96%; Length: 14m
How Master Theorem Solve Recurrence Relations| Example#1 | All Cases Explained with Example Views: 14.7K; Net Likes: 272; Like Ratio: 96%; Length: 6m
Chapter 3.5: Master Method for Solving Recurrences
Algorithms lecture 5 -- Masters theorem Views: 453K; Net Likes: 2.24K; Like Ratio: 97%; Length: 24m
Master Theorem Views: 170K; Net Likes: 2.14K; Like Ratio: 96%; Length: 5m
Master Method ( incl. Step-By-Step Guide and Examples ) - Analysis Views: 95.9K; Net Likes: 2.12K; Like Ratio: 99%; Length: 16m
Master Theorem Example Views: 43.1K; Net Likes: 365; Like Ratio: 96%; Length: 7m
Chapter 4
Chapter 4.1: Stacks and Queues
Data Structures: Stacks and Queues Views: 279K; Net Likes: 2.5K; Like Ratio: 97%; Length: 5m
Stacks and Queues Views: 346K; Net Likes: 2.04K; Like Ratio: 96%; Length: 16m
3.1 Stack in data structure | Introduction to stack | data structures Views: 68.4K; Net Likes: 1.12K; Like Ratio: 98%; Length: 17m
Swift Interview Algorithms: Stacks and Generics Views: 23.4K; Net Likes: 786; Like Ratio: 99%; Length: 13m
Chapter 4.2: Linked Lists
Introduction to Linked Lists (Data Structures & Algorithms #5) Views: 320K; Net Likes: 6.08K; Like Ratio: 99%; Length: 18m
Data Structures: Linked Lists Views: 503K; Net Likes: 5.29K; Like Ratio: 97%; Length: 7m
Introduction to Linked List in Data Structures ( very easy) Views: 354K; Net Likes: 4.36K; Like Ratio: 95%; Length: 14m
How Linked List will screw your Interview - Do this in O(1) space! Views: 122K; Net Likes: 3.23K; Like Ratio: 95%; Length: 14m
Chapter 4.3: Hash Tables
What is a HashTable Data Structure - Introduction to Hash Tables , Part 0 Views: 927K; Net Likes: 8.65K; Like Ratio: 96%; Length: 7m
Hashing Technique - Simplified Views: 324K; Net Likes: 4.88K; Like Ratio: 98%; Length: 17m
8. Hashing with Chaining Views: 379K; Net Likes: 2.88K; Like Ratio: 99%; Length: 51m
Java Hash Table Views: 361K; Net Likes: 2.78K; Like Ratio: 95%; Length: 13m
Chapter 4.4: Binary Search Trees
Data structures: Binary Search Tree Views: 910K; Net Likes: 5.7K; Like Ratio: 97%; Length: 19m
Java Binary Search Tree Views: 455K; Net Likes: 4.02K; Like Ratio: 97%; Length: 13m
Algorithms: Binary Search Views: 438K; Net Likes: 3.29K; Like Ratio: 95%; Length: 6m
5.10 Binary Search Trees (BST) - Insertion and Deletion Explained Views: 167K; Net Likes: 2.97K; Like Ratio: 97%; Length: 16m
Chapter 4.5: Red-Black Trees
5.17 Red Black Tree Insertion Views: 59.1K; Net Likes: 948; Like Ratio: 96%; Length: 27m
Red Black Trees 2 Example of building a tree Views: 51.3K; Net Likes: 929; Like Ratio: 99%; Length: 17m
5.18 Red Black Tree deletion | Data structure Views: 36.8K; Net Likes: 606; Like Ratio: 97%; Length: 1H3m
Red Black Tree 1 The Rules Views: 36.2K; Net Likes: 513; Like Ratio: 99%; Length: 8m
Chapter 5
Chapter 5.1: B-Trees
B-Tree Tutorial - An Introduction to B-Trees Views: 158K; Net Likes: 2.42K; Like Ratio: 97%; Length: 12m
5.28 B tree deletion in data structures Views: 92.9K; Net Likes: 1.79K; Like Ratio: 98%; Length: 28m
5.29 B+ tree insertion | B+ tree creation example | Data structure Views: 88.1K; Net Likes: 1.45K; Like Ratio: 97%; Length: 18m
5.27 Insertion in B-Tree of Order 4 (Data Structure) Views: 81.9K; Net Likes: 1.31K; Like Ratio: 97%; Length: 15m
Chapter 5.2: Fibonacci Heaps
Fibonacci heap Views: 17.8K; Net Likes: 392; Like Ratio: 98%; Length: 21m
Amortized analysis of Fibonacci heap Views: 5.39K; Net Likes: 76; Like Ratio: 99%; Length: 36m
Chapter 5.3: van Emde Boas Trees
Advanced Algorithms (COMPSCI 224), Lecture 2 Views: 52.1K; Net Likes: 293; Like Ratio: 96%; Length: 1H25m
Episode 12 - Divide and Conquer on Trees Views: 7.31K; Net Likes: 147; Like Ratio: 100%; Length: 1H13m
Integer I - Advanced data structures Views: 7.16K; Net Likes: 40; Like Ratio: 98%; Length: 1H20m
Cache Oblivious Search Views: 1.74K; Net Likes: 18; Like Ratio: 100%; Length: 3m
Chapter 5.4: Data Structures for Disjoint Sets
1.12 Disjoint Sets Data Structure - Weighted Union and Collapsing Find Views: 195K; Net Likes: 2.94K; Like Ratio: 98%; Length: 26m
Practical Programming Algorithm: Disjoint Sets Views: 52.7K; Net Likes: 608; Like Ratio: 98%; Length: 14m
Disjoint Sets - Data Structures in 5 Minutes Views: 40.7K; Net Likes: 436; Like Ratio: 96%; Length: 7m
Chapter-14: Disjoint Sets and their Representations Views: 2.1K; Net Likes: 21; Like Ratio: 100%; Length: 5m
Chapter 6
Chapter 6.1: Introduction to Graph Theory
Data structures: Introduction to graphs Views: 622K; Net Likes: 5.94K; Like Ratio: 98%; Length: 16m
Graph Theory - An Introduction! Views: 507K; Net Likes: 4.52K; Like Ratio: 98%; Length: 12m
[Discrete Mathematics] Introduction to Graph Theory Views: 259K; Net Likes: 2.52K; Like Ratio: 97%; Length: 33m
Graph Theory Introduction Views: 44.9K; Net Likes: 729; Like Ratio: 99%; Length: 14m
Chapter 6.2: Breadth-First Search and Depth-First Search
13. Breadth-First Search (BFS) Views: 487K; Net Likes: 3.49K; Like Ratio: 98%; Length: 50m
6.2 BFS and DFS Graph Traversals| Breadth First Search and Depth First Search | Data structures Views: 208K; Net Likes: 3.19K; Like Ratio: 96%; Length: 20m
Binary tree traversal - breadth-first and depth-first strategies Views: 502K; Net Likes: 2.86K; Like Ratio: 96%; Length: 11m
14. Depth-First Search (DFS), Topological Sort Views: 297K; Net Likes: 1.86K; Like Ratio: 98%; Length: 50m
Chapter 6.4: Minimum Spanning Trees
Prim's Algorithm: Minimal Spanning Tree Views: 271K; Net Likes: 2.18K; Like Ratio: 99%; Length: 6m
6.5 Prim's Algorithm for Minimum Spanning Tree | Data structures Views: 126K; Net Likes: 2.02K; Like Ratio: 97%; Length: 10m
6.6 Kruskals Algorithm for Minimum Spanning Tree- Greedy method | Data structures Views: 80.8K; Net Likes: 1.42K; Like Ratio: 98%; Length: 9m
Kruskal's Algorithm: Minimum Spanning Tree (MST) Views: 155K; Net Likes: 999; Like Ratio: 96%; Length: 6m
Chapter 6.5: Kruskal's and Prim's Algorithms
6.5 Prim's Algorithm for Minimum Spanning Tree | Data structures Views: 126K; Net Likes: 2.02K; Like Ratio: 97%; Length: 10m
6.6 Kruskals Algorithm for Minimum Spanning Tree- Greedy method | Data structures Views: 80.8K; Net Likes: 1.42K; Like Ratio: 98%; Length: 9m
Kruskal's Algorithm: Minimum Spanning Tree (MST) Views: 155K; Net Likes: 999; Like Ratio: 96%; Length: 6m
Minimum Spanning Tree - Kruskal and Prim algorithms Views: 36.1K; Net Likes: 338; Like Ratio: 96%; Length: 5m
Chapter 6.6: Bellman-Ford Algorithm
6.14 Bellman Ford Algorithm-Single Source Shortest Path | Dynamic Programming Views: 76K; Net Likes: 1.02K; Like Ratio: 96%; Length: 15m
17. Bellman-Ford Views: 133K; Net Likes: 613; Like Ratio: 96%; Length: 48m
Bellman Ford Algorithm | Graph Theory Views: 35.6K; Net Likes: 453; Like Ratio: 96%; Length: 15m
Bellman Ford Algorithm Example Views: 16K; Net Likes: 167; Like Ratio: 96%; Length: 12m
Chapter 6.7: Dijkstra’s Algorithm
3.6 Dijkstra Algorithm - Single Source Shortest Path - Greedy Method Views: 1M; Net Likes: 12.5K; Like Ratio: 97%; Length: 18m
Dijkstra's Algorithm: Another example Views: 584K; Net Likes: 4.89K; Like Ratio: 98%; Length: 8m
6.13 Dijkstra Algorithm- single source shortest path| With example | Greedy Method Views: 136K; Net Likes: 1.88K; Like Ratio: 96%; Length: 34m
16. Dijkstra Views: 204K; Net Likes: 1.11K; Like Ratio: 96%; Length: 51m
Chapter 6.8: Floyd-Warshall Algorithm
6.15 Floyd Warshall Algorithm All Pair Shortest Path algorithm | data structures and algorithms Views: 87.8K; Net Likes: 1.45K; Like Ratio: 96%; Length: 31m
11. Dynamic Programming: All-Pairs Shortest Paths Views: 52.3K; Net Likes: 421; Like Ratio: 98%; Length: 1H21m
Floyd Warshall All Pairs Shortest Path Algorithm | Graph Theory Views: 16.8K; Net Likes: 322; Like Ratio: 98%; Length: 15m
Chapter 6.9: Ford-Fulkerson Method
Network Flows: Max-Flow Min-Cut Theorem (& Ford-Fulkerson Algorithm) Views: 39.9K; Net Likes: 848; Like Ratio: 95%; Length: 21m
Ford-Fulkerson Algorithm Views: 63K; Net Likes: 507; Like Ratio: 98%; Length: 9m
Introduction to Network Flow and Ford-Fulkerson Algorithm Views: 65.6K; Net Likes: 431; Like Ratio: 98%; Length: 43m
Ford Fulkerson Algorithm - How to Create a Residual Graph in a Network Flow Views: 9.72K; Net Likes: 171; Like Ratio: 99%; Length: 8m
Chapter 6.10: Bipartite Matching Problem
Decision 1 (D1) - Matchings - Bipartite Graphs and Maximum Matching Algorithm Views: 36K; Net Likes: 132; Like Ratio: 97%; Length: 41m
Maximum bipartite matching graph problem in Tamil | daa |how to pass in design&analysis of algorithm Views: 1.6K; Net Likes: 54; Like Ratio: 97%; Length: 14m
A Second Course in Algorithms (Lecture 5: Minimum-Cost Bipartite Matching) Views: 4.81K; Net Likes: 49; Like Ratio: 100%; Length: 1H21m
Maximal Flow solution to bipartite matching problem and Minimal Spanning Tree Views: 1.1K; Net Likes: 7; Like Ratio: 100%; Length: 29m
Chapter 7
Chapter 7.1: Introduction to Dynamic Programming
19. Dynamic Programming I: Fibonacci, Shortest Paths Views: 1.35M; Net Likes: 13.6K; Like Ratio: 98%; Length: 51m
Algorithms: Memoization and Dynamic Programming Views: 612K; Net Likes: 7.1K; Like Ratio: 97%; Length: 11m
4 Principle of Optimality - Dynamic Programming introduction Views: 321K; Net Likes: 3.92K; Like Ratio: 98%; Length: 14m
What is Dynamic Programming and how is it done? Views: 76K; Net Likes: 2.3K; Like Ratio: 96%; Length: 3m
Chapter 7.2: Knapsack Problem
4.5 0/1 Knapsack - Two Methods - Dynamic Programming Views: 736K; Net Likes: 7.54K; Like Ratio: 96%; Length: 28m
The 0/1 Knapsack Problem (Demystifying Dynamic Programming) Views: 49.8K; Net Likes: 1.35K; Like Ratio: 95%; Length: 20m
0/1 knapsack problem-Dynamic Programming | Data structures and algorithms Views: 88.2K; Net Likes: 1.34K; Like Ratio: 96%; Length: 27m
Fractional Knapsack Problem using Greedy Method | Example | Data structures and algorithms Views: 47.6K; Net Likes: 685; Like Ratio: 97%; Length: 11m
Chapter 7.3: Longest Common Subsequence
Longest Common Subsequence (2 Strings) - Dynamic Programming & Competing Subproblems Views: 41.8K; Net Likes: 2.12K; Like Ratio: 100%; Length: 25m
Longest Common Subsequence (Dynamic Programming) Views: 88.3K; Net Likes: 1.24K; Like Ratio: 95%; Length: 10m
Longest common subsequence algorithm -- example Views: 93.2K; Net Likes: 1.11K; Like Ratio: 99%; Length: 8m
Longest Common Subsequence Dynamic Programming : Interview question Views: 42.3K; Net Likes: 570; Like Ratio: 97%; Length: 19m
Chapter 7.4: Optimal Binary Search Trees
OPTIMAL BINARY SEARCH TREE WITH EXAMPLE USING DYNAMIC PROGRAMMING- ALGORITHMS Views: 6.1K; Net Likes: 99; Like Ratio: 97%; Length: 31m
Dynamic Programming: Optimal Binary Search Trees Part 1 Views: 2.3K; Net Likes: 58; Like Ratio: 98%; Length: 7m
Dynamic Programming: Optimal Binary Search Trees Part 5 Views: 868; Net Likes: 27; Like Ratio: 100%; Length: 9m
ALGORITHM FOR OPTIMAL BINARY SEARCH TREE IN DYNAMIC PROGRAMMING Views: 1.03K; Net Likes: 20; Like Ratio: 100%; Length: 15m
Chapter 7.5: Coin Change Problem
Coin Change Problem (Dynamic Programming) Views: 121K; Net Likes: 1.72K; Like Ratio: 96%; Length: 10m
Total Unique Ways To Make Change - Dynamic Programming ("Coin Change 2" on LeetCode) Views: 53.7K; Net Likes: 1.7K; Like Ratio: 97%; Length: 11m
AMAZON CODING INTERVIEW QUESTION - COIN CHANGE (LeetCode) Views: 31.8K; Net Likes: 755; Like Ratio: 97%; Length: 10m
Coin Change Problem: Minimum number of coins Dynamic Programming Views: 26.4K; Net Likes: 461; Like Ratio: 97%; Length: 27m
Chapter 7.6: Rod Cutting Problem
14 Rod Cutting Problem Views: 3.43K; Net Likes: 136; Like Ratio: 99%; Length: 18m
Algorithms 15.1 - dynamic programming rod cutting Views: 5.18K; Net Likes: 86; Like Ratio: 96%; Length: 24m
Rod Cutting Problem Algorithm Implementation DP Views: 61; Net Likes: 1; Like Ratio: 100%; Length: 18m
050 Rod cutting problem example Java | Algorithm | Data Structure Views: 36; Net Likes: 1; Like Ratio: 100%; Length: 8m
Chapter 8
Chapter 8.1: Introduction ot Greedy Algorithms
Introduction to Greedy Algorithms | GeeksforGeeks Views: 285K; Net Likes: 1.98K; Like Ratio: 96%; Length: 5m
12. Greedy Algorithms: Minimum Spanning Tree Views: 114K; Net Likes: 968; Like Ratio: 98%; Length: 1H22m
Introduction to Greedy Techniques With Example | What is Greedy Techniques Views: 7.86K; Net Likes: 285; Like Ratio: 99%; Length: 7m
Introduction To Greedy Method l Design And Analysis Of Algorithm Course Views: 3.06K; Net Likes: 137; Like Ratio: 98%; Length: 9m
Chapter 8.2: Activity-Selection Problem
Greedy Algorithms | Set 1 (Activity Selection Problem) | GeeksforGeeks Views: 138K; Net Likes: 752; Like Ratio: 97%; Length: 5m
Interval Scheduling Maximization (Proof w/ Exchange Argument) Views: 9.31K; Net Likes: 283; Like Ratio: 99%; Length: 20m
Weighted Job Scheduling / Sequencing using Dynamic Programming Views: 15K; Net Likes: 182; Like Ratio: 98%; Length: 20m
DAA62: Activity Selection Problem using Greedy Algorithm| Greedy Activity Selection Problem example Views: 5.26K; Net Likes: 53; Like Ratio: 98%; Length: 16m
Chapter 8.3: Huffman Codes
Huffman Coding - Greedy Algorithm Views: 369K; Net Likes: 3.84K; Like Ratio: 96%; Length: 8m
How Huffman Trees Work - Computerphile Views: 201K; Net Likes: 3.41K; Like Ratio: 99%; Length: 11m
9.1 Huffman coding example -Greedy Method |Data Structures Views: 37.3K; Net Likes: 610; Like Ratio: 97%; Length: 34m
Huffman Coding (Lossless Compression Algorithm) Views: 19.5K; Net Likes: 300; Like Ratio: 97%; Length: 10m
Chapter 8.4: Inverval Scheudling
Max Contiguous Subarray Sum - Cubic Time To Kadane's Algorithm ("Maximum Subarray" on LeetCode) Views: 69.5K; Net Likes: 2.69K; Like Ratio: 98%; Length: 19m
1. Course Overview, Interval Scheduling Views: 285K; Net Likes: 1.7K; Like Ratio: 99%; Length: 1H23m
Network Flows: Max-Flow Min-Cut Theorem (& Ford-Fulkerson Algorithm) Views: 39.9K; Net Likes: 848; Like Ratio: 95%; Length: 21m
Greedy Algorithms for Time-Slot Interval Optimization Views: 32.7K; Net Likes: 495; Like Ratio: 95%; Length: 11m
Chapter 8.5: Shortest Paths in a Graph
3.6 Dijkstra Algorithm - Single Source Shortest Path - Greedy Method Views: 1M; Net Likes: 12.5K; Like Ratio: 97%; Length: 18m
6.13 Dijkstra Algorithm- single source shortest path| With example | Greedy Method Views: 136K; Net Likes: 1.88K; Like Ratio: 96%; Length: 34m
15. Single-Source Shortest Paths Problem Views: 162K; Net Likes: 754; Like Ratio: 96%; Length: 53m
Shortest/Longest path on a Directed Acyclic Graph (DAG) | Graph Theory Views: 36.7K; Net Likes: 433; Like Ratio: 98%; Length: 9m
Chapter 9
Chapter 9.1: The Hiring Problem
What is Randomized Algorithm in Analysis of Algorithm Views: 2.89K; Net Likes: 26; Like Ratio: 96%; Length: 8m
Randomization algorithm Hiring problem Views: 12; Net Likes: 2; Like Ratio: 100%; Length: 14m
Epi 07: Solving The Hiring Problem with AI Views: 324; Net Likes: 2; Like Ratio: 100%; Length: 2m
Hiring problem Views: 19; Net Likes: 1; Like Ratio: 100%; Length: 2m
Chapter 9.2: Randomized Algorithms
Randomized algorithms lecture #1 - probability, repeating a process Views: 16K; Net Likes: 579; Like Ratio: 99%; Length: 22m
Lec 4 | MIT 6.046J / 18.410J Introduction to Algorithms (SMA 5503), Fall 2005 Views: 137K; Net Likes: 339; Like Ratio: 97%; Length: 1H20m
Randomized algorithms lecture #2 - birthday paradox, random shuffle, hashing Views: 8.81K; Net Likes: 329; Like Ratio: 99%; Length: 21m
6. Randomization: Matrix Multiply, Quicksort Views: 30.3K; Net Likes: 224; Like Ratio: 98%; Length: 1H21m
Chapter 9.3: Hashing: A Randomized Implementation of Dictionaries
8. Hashing with Chaining Views: 379K; Net Likes: 2.88K; Like Ratio: 99%; Length: 51m
8.1 Hashing techniques to resolve collision| Separate chaining and Linear Probing | Data structure Views: 104K; Net Likes: 1.44K; Like Ratio: 97%; Length: 25m
8. Randomization: Universal & Perfect Hashing Views: 38.9K; Net Likes: 358; Like Ratio: 98%; Length: 1H21m
10. Dictionaries Views: 11.5K; Net Likes: 67; Like Ratio: 99%; Length: 1H23m