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There are usually multiple ways to solve the problem using a computer program. For instance, there are several ways to sort items in an array - you can use merge sort, bubble sort, insertion sort, and so on. All of these algorithms have their own pros and cons and the...
Usman Malik
The K-nearest Neighbors (KNN) algorithm is a type of supervised machine learning algorithm used for classification, regression as well as outlier detection. It is extremely easy to implement in its most basic form but can perform fairly complex tasks. It is a lazy learning algorithm since it doesn't have a...
Cássia Sampaio
K-means clustering is an unsupervised learning algorithm that groups data based on each point euclidean distance to a central point called centroid. The centroids are defined by the means of all points that are in the same cluster. The algorithm first chooses random points as centroids and then iterates adjusting...
K-Means clustering is one of the most widely used unsupervised machine learning algorithms that form clusters of data based on the similarity between data instances. In this guide, we will first take a look at a simple example to understand how the K-Means algorithm works before implementing it using Scikit-Learn....
If you had studied longer, would your overall scores get any better? One way of answering this question is by having data on how long you studied for and what scores you got. We can then try to see if there is a pattern in that data, and if in...
Graphs are one of the most useful data structures. They can be used to model practically everything - object relations and networks being the most common ones. An image can be represented as a grid-like graph of pixels, and sentences can be represented as graphs of words. Graphs are used...
Anđela Niketić
Originating from mathematics, graphs are now widely used data structures in Computer Science. One of the first problems we encounter when constructing any algorithm regarding Graph processing or traversal is how we represent the graph and then, how to traverse that representation. Graph traversal is not a trivial problem, and...
Graphs in Python can be represented in several different ways. The most notable ones are adjacency matrices, adjacency lists, and lists of edges. In this guide, we'll cover all of them. When implementing graphs, you can switch between these types of representations at your leisure. First of all, we'll quickly...
Dimitrije Stamenic
A graph is a great tool for modeling relationships between objects. Graphs can model complex relationships between any number of objects in a system, which makes them ideal for representing interactions between concepts/items in areas like physics, economics, chemistry. Thanks to constantly increasing computational power, you can manipulate graphs...
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