Amazing Graph Algorithms Coding in JavaJavaScript Python
What you’ll learn
Graph Algorithms
Programming Algorithms
Requirements
No
Description
Graphs are Amazing! We will have a lot to cover in this course also the course is coded in Java, JavaScript & Python.While solving graph algorithms, We may need to visit and process each node present in the graph. And for that, we must know how to traverse the graphs efficiently,So, first, we will cover graph traversal, where we gonna see the 2 types of graph traversals, Depth First Search, and Breadth-first Search.Then we will understand Spanning Trees and will see famous algorithms to find minimum cost spanning tree, basically, a minimum cost spanning tree is a tree from the graph connecting all the vertices with single edges each and that allOf the lowest cost, so to minimize the cost to connect all the vertices.For example :Suppose, you own a telecommunication company and you have towers that spread across the state. You want to connect them so that data can be passed from one tower to others.Connecting different towers involve different costs, so the problem is how will you minimize the cost. Here, comes the need of using Minimum spanning tree algorithms to findThat tree connecting all the towers with edges that have a minimum cost, so that the spanning Tree cost is minimum.After that, we will look to Shortest Path algorithms, these are useful to find the shortest distance from of a source from all the other vertices (called single-source shortest path) or shortest distance of each vertex with all the Other vertices, that’s called finding all pair shortest path.For example, finding the distance of a city, let’s say Istambul to all the other famous cities of turkey.Or let’s say A person who is planning a trip may need to answer questions such as, “What is the least expensive way to get from Princeton to San Jose?” A person more interested in time than in money may need to know the answer to the question “What is the fastest way to get from Princeton to San Jose?” To answer such questions, we process information about connections (travel routes) between items (towns and cities).Then we will move to Flow network problems. These are concerned with the networks or graph, having a flow going through it. There will be problems that ask to maximize the flow across the network or problems that ask to disconnect the source from the destination or sink in minimum cost.After that we will discuss, algorithms to find strongly connected components in a graph.Hope you will enjoy the course.Happy Learning
Overview
Section 1: Understanding Graphs
Lecture 1 Graphs – In Real World
Lecture 2 Google’s Knowledge Graph
Lecture 3 Graphs – Overview
Lecture 4 Terminologies
Lecture 5 Identification of Problem
Lecture 6 Approaching the Problem
Lecture 7 Journey : What We Are Going To Cover
Section 2: Let’s Get Started
Lecture 8 Course Resources
Section 3: Graph Traversal Algorithms
Lecture 9 Graph Traversal
Lecture 10 Depth First Search Traversal – DFS
Lecture 11 DFS – Recursive Java Implementation
Lecture 12 DFS – Iterative Java Implementation
Lecture 13 DFS – Recursive Javascript Implementation
Lecture 14 DFS – Iterative Javascript Implementation
Lecture 15 DFS – Recursive Python Implementation
Lecture 16 DFS – Complexity Analysis
Lecture 17 Breadth First Search Traversal
Lecture 18 BFS – Java Implementation
Lecture 19 BFS – Javascript Implementation
Lecture 20 BFS – Python Implementation
Lecture 21 BFS – Complexity Analysis
Section 4: Minimum Spanning Tree Algorithms
Lecture 22 What Are Spanning Trees; What is MST?
Lecture 23 Prim’s Algorithm
Lecture 24 Prim’s Algorithm – Java Implementation
Lecture 25 Prim’s Algorithm – Javascript Implementation
Lecture 26 Prim’s Algorithm – Python Implementation
Lecture 27 Kruskal’s Algorithm
Lecture 28 Union-Find Algorithm
Lecture 29 Kruskal’s Algorithm – java Implementation
Lecture 30 Kruskal’s Algorithm – Javascript Implementation
Lecture 31 Kruskal’s Algorithm – Python Implementation
Section 5: Shortest Path Algorithms
Lecture 32 Finding Shortest Path
Lecture 33 Dijkstra’s Algorithm
Lecture 34 Dijkstra’s Algorithm – Java Implementation
Lecture 35 Dijkstra’s Algorithm – Javascript Implementation
Lecture 36 Dijkstra’s Algorithm – Python Implementation
Lecture 37 BellmanFord’s Algo
Lecture 38 BellmanFord’s Algo Live Code Java
Lecture 39 BellmanFord’s Algo Live Code Javascript
Lecture 40 BellmanFord’s Algo Live Code Python
Lecture 41 Floyd Warshall Algorithm
Lecture 42 Floyd-Warshall Algorithm – Java Implementation
Lecture 43 Floyd-Warshall Algorithm – Javascript Implementation
Lecture 44 Floyd-Warshall Algorithm – Python Implementation
Lecture 45 Johnson’s Algorithm
Lecture 46 Johnson’s Algorithm – Java Implementation
Lecture 47 Johnson’s Algorithm – Javascript Implementation
Lecture 48 Johnson’s Algorithm – Python Implementation
Section 6: Network Flow Algorithms
Lecture 49 What Are Flow Networks?
Lecture 50 Ford-Fulkerson Algorithm
Lecture 51 Ford-Fulkerson Algorithm – Edmond’s Karp Java Implementation
Lecture 52 Ford-Fulkerson Algorithm – Edmond’s Karp Javascript Implementation
Lecture 53 Ford-Fulkerson Algorithm – Edmond’s Karp Python Implementation
Lecture 54 Max-Flow Min-Cut Theorem
Section 7: Strongly Connected Components
Lecture 55 Strongly Connected Components
Lecture 56 Tarjan’s Algorithm
Lecture 57 Tarjan’s Algorithm – Java Implementation
Lecture 58 Tarjan’s Algorithm – Javascript Implementation
Lecture 59 Tarjan’s Algorithm – Python Implementation
Lecture 60 Kosaraju’s Algorithm
Lecture 61 Kosaraju’s Algorithm – Java Implementation
Lecture 62 Kosaraju’s Algorithm – Javascript Implementation
Lecture 63 Kosaraju’s Algorithm – Python Implementation
Section 8: Others
Lecture 64 Topological Sort : Kahn’s Algo
Lecture 65 Topological Sort Live Code Java
Lecture 66 Topological Sort Live Code Javascript
Lecture 67 Topological Sort Live Code Python
Section 9: Thank You
Lecture 68 Thank you!
Who wants to deep dive into graphs,Want to solve some super complicated graph Algorithms
Course Information:
Udemy | English | 9h 0m | 1.92 GB
Created by: Basics Strong
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