Algorithm

1. What’s an algorithm?

An algorithm is a set of well-defined and ordered instructions or rules that describe, step by step, how to carry out a task or solve a particular problem. In computer science and computer science, algorithms are fundamental to software development and efficient problem solving. Algorithms always consist of a mathematical formula that acts as a logical foundation by which the algorithm performs the actions for which it was designed, usually searching for routes in graphs, learning from data, applying grouping equations, averaging, regression, etc.

2. What’s the algorithm function?

Algorithms are fundamental tools in computing and problem solving, playing a crucial role in various aspects of digital life. Its usefulness lies in its ability to provide efficient and structured solutions to a wide range of problems, from searching and classifying data to optimizing complex processes. Algorithms allow you to automate tasks, perform precise calculations and make logical decisions in real time. In programming, they guide the creation of software, determining how applications work and respond to various situations. Additionally, in fields such as artificial intelligence, machine learning algorithms are used to extract patterns and insights from data, driving significant advances in fields such as speech recognition, computer vision, and autonomous decision-making. In short, algorithms are the foundation of computing, providing the ability to systematically and efficiently solve problems in the digital age.

Algorithms differ from models in the output of the final result, since the model is essentially an algorithm, but it is considered a model when the final result of learning or calculating the data is stored for later use, whether in binary format. or as an HTTP request response in a REST API, for example, a random forest is an embedded algorithm, but said algorithm is trained with toxic mushroom data to classify whether or not a mushroom can be toxic and also said training and testing data are loaded into a REST API to test it with new mushroom data, that makes the random forest a machine learning model (and not an algorithm) put into production.

3. Example of algorithms.

• Decision tree.
• Random Forest.
• Voronoi.
• A*.
• CNN.
• RNN.
• Kruskal algorithm.