Machine learning and artificial intelligence (AI) are playing an increasingly important role in modeling and classification based on patterns, including in online marketing . Companies such as Tesla, Google, Microsoft, Amazon and Facebook are investing a great deal of research into artificial intelligence.
Since Google announced in November 2015 that a new, very important ranking signal or important ranking factor called Rankbrain has been in use for months, interest in the subject of machine learning has finally arrived in the SEO and online marketing community. I consider the subject of machine learning, especially in a digital context, to be just as radical and forward-looking as, for example, mobile, big data and content marketing . I would like to explain below how machine learning is related to other current buzzwords such as artificial intelligence , semantics or deep learning and what effects this development towards self-learning algorithms has bulgaria phone number data on search engines . I would like to point out that I have only been able to look at the subject of artificial intelligence or machine learning superficially. If you would like to delve deeper into the subject, you will find a detailed collection of videos and links to sources on the subject at the end of the article.
What is Machine Learning? Meaning, Definition & Methodology
The current and especially future importance of machine learning can be classified in a similar way to the topics of mobile, big data or content marketing in a digital context . The frequency of media presence of these topics has also increased significantly since 2014, as can be seen on Google Trends.
Google Trends: Development of search volume for big data, machine learning and content marketing
Google Trends: Worldwide development of search volume for Big Data (yellow), Machine Learning (blue) and Content Marketing (red)
As I have already explained in my article The Semantic Web (Web 3.0) as a logical consequence of Web 2.0, systems that make information identifiable, categorizable, assessable and sortable depending on the context are the only way to master the flood of information and data based on the innovations of Web 2.0. But pure semantics are not enough here. That is why digital gatekeepers need increasingly reliable algorithms to accomplish this task. In the future, self-learning algorithms based on artificial intelligence and machine learning methods will play an increasingly important role here. This is the only way to ensure the relevance of results and outputs/results that conform to expectations.