Graph in Data Structure and Algorithm: A graph in data structure can be thought of as a data structure that is used to describe relationships between entities. Learn more.
Greedy Algorithm Greedy algorithms aim for the best solution at the moment without considering future consequences. They are used in problem solving, such as the Kruskal’s and Prim’s algorithms for finding the minimum spanning tree in a graph. Backtracking Algorithm This type is used in constrai...
An algorithm is, in its purest sense, a mathematical process for solving a problem using a finite number of steps. In the world ofcomputers, we define an algorithm as a set of instructions that specifies not only what needs to be done but how to do it. It processes inputs, such as n...
OSPF uses the shortest path first (SPF) algorithm to calculate routes, resulting in fast route convergence. Adjacency Establishment Adjacencies can be established in either of the following situations: Two routers have established a neighbor relationship and communicate for the first time. ...
It uses the SPF algorithm, ensuring fast convergence. It applies to large networks, such as Internet service provider (ISP) networks. What Are the Basic Concepts of IS-IS? IS-IS Router Types To support large-scaleroutingnetworks, IS-IS adopts a two-level structure in a routing domain. A ...
Hash functions, like the Secure Hash Algorithm 1 (SHA-1), can transform an input into a string of characters of a fixed length, which is unique to the original data. This hash value helps in verifying the integrity of data by making it computationally infeasible to find two different input...
you should use a stack when you need to access elements in a lifo manner, such as when implementing undo functionality, parsing expressions, or doing depth-first search in a graph. on the other hand, queues are better suited for scenarios where you need first-in-first-out (fifo) access,...
A CNN is a category of ML model and deep learning algorithm that's well suited to analyzing visual data sets. CNNs use principles from linear algebra, particularly convolution operations, to extract features and identify patterns within images. CNNs are predominantly used to process images, but ...
More specifically, machine learning creates an algorithm or statistical formula (referred to as a “model”) that converts a series of data points into a single result. ML algorithms “learn” through “training,” in which they identify patterns and correlations in data and use them to provid...
Clustering is an unsupervised learning method that organizes your data in groups with similar characteristics. Explore videos, examples, and documentation.