This in-depth exploration will help you understand and harness the power of these fundamental data structures.
What is a Graph?
In data structures, a graph is a collection of nodes (vertices) connected by edges. These connections can represent relationships between various entities or data points. Graphs are used to model complex networks, such as social media connections, transportation routes, and more, providing a versatile way to visualize and analyze interconnected data.
What is DSA?
DSA stands for Data Structures and Algorithms. It refers to a set of techniques and methods used to organise and manipulate data in a computer program. Data structures are a way of organising and storing data in a way that enables efficient access and modification, while algorithms are a set of instructions that perform a specific task or solve a problem.
What is data structure?
A data structure is a way of organising and storing data in a computer program so that it can be accessed and manipulated efficiently. It defines a set of rules for how data is organised, how it is accessed, and how operations can be performed on it. Examples include arrays, linked lists, and trees.
What is an algorithm?
An algorithm is a set of instructions for solving a problem or performing a task in a computer program. It defines a series of steps or procedures that must be followed in order to achieve a desired outcome. Algorithms are used in a wide range of applications, from search engines to robotics.
Types of DSA
There are many types of Data Structures and Algorithms (DSA) including arrays, linked lists, stacks, queues, trees, graphs, hash tables, and sorting and searching algorithms. Each DSA has its own strengths and weaknesses and is suitable for different types of data processing and storage needs.
Applications of DS
Data Structures have a wide range of applications in computer science, including database management, algorithm design and analysis, operating systems, artificial intelligence, machine learning, and web development. They are used to store, organise, and manipulate large amounts of data efficiently and effectively, enabling faster and more accurate processing of information.
Topics covered:
0:00 – Introduction and Agenda
0:39 – Introduction to Graph Data Structure
19:23 – Edge list, Adjacency Matrix and Adjacency List
55:49 – Introduction to Graph Traversal and Breadth First Search (BFS)
1:00:02 – Breadth First Search (Code implementation)
1:43:59 – Depth First Search (Code implementation)
2:28:46 – Introduction to Flood Fill Algorithm (Code implementation)
3:06:28 – Topological Sorting (Code implementation)
3:37:37 – Travelling Salesman Problem
4:27:33 – Dijkstra’s Algorithm
#graphtheory #dsa #datastructures #algorithm #scaler #softwareengineering
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