Artificial intelligence

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AI & Algorithms: Regression

By Magnus Unemyr / April 15, 2019 / 0 Comments

Now that other blog posts in this article series have helped us  understand different types of variables, let’s look at some ways they can relate to each other, and how that can help us understand sets of data. The first and more straightforward group of algorithms use regression. This is a way of looking at

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AI & Algorithms: Clustering

By Magnus Unemyr / April 15, 2019 / 0 Comments

As seen in the previous blog posts in this article serie (the first blog post in the serie was Understanding AI Algorithms), we can classify data into defined groups in a number of ways. However, what if we don’t know a lot about our data? This is where clustering algorithms step in. A cluster is

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AI & Algorithms: Classification

By Magnus Unemyr / April 15, 2019 / 0 Comments

This blog post on classification algorithms is part of the article series Understanding AI Algorithms. Classification algorithms, also known as classifiers, are used to put observations into defined groups. For example, it is known that some customers respond well to marketing emails, and some do not. Wouldn’t it be great to know which customers will respond

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AI & Algorithms: Agglomerative Hierarchical Clustering

By Magnus Unemyr / April 15, 2019 / 0 Comments

This blog post on the Agglomerative Hierarchical Clustering algorithm (which is a clustering algorithm) is part of the blog post series Understanding AI Algorithms. Sometimes when looking at a set of data, the number of clusters isn’t distinct. This is where agglomerativehierarchical clustering is useful. Imagine that you just launched a new product and you

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AI & Algorithms: DBSCAN

By Magnus Unemyr / April 15, 2019 / 0 Comments

This blog post on the DBSCAN algoritm is part of the article series Understanding AI Algorithms. DBSCAN is a clustering algorithm. The density-based spatial clustering of applications with noise algorithm (DBSCAN) uses clustering by finding groups of observations with a high density, meaning they are not spread out. This is appropriate if the clusters can

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AI & Algorithms: K-Means

By Magnus Unemyr / April 15, 2019 / 0 Comments

This blog post on the K-Means algorithm is part of the article series Understanding AI Algorithms. K-Means is a clustering algorithm. K-Means is an algorithm that segments data into clusters to study similarities. This includes information on customer behavior, which can be used for targeted marketing. The system looks at similarities between observations (for example,

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