Amazing Graph Algorithms Coding in JavaJavaScript Python

Graph Data Structure, DFS, BFS, Minimum Spanning Tree, Shortest Path, Network Flow, Strongly Connected Components
Amazing Graph Algorithms Coding in JavaJavaScript Python
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1.92 GB
Total length :
9h 0m



Basics Strong


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Amazing Graph Algorithms Coding in JavaJavaScript Python

What you’ll learn

Graph Algorithms
Programming Algorithms

Amazing Graph Algorithms Coding in JavaJavaScript Python




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


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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