Machine Learning

Machine Learning is an important area of computer technology and a component of artificial intelligence. Computer programs which are based on machine learning can find independent solutions for new and unknown problems with the help of algorithms. Machine Learning is also used in Online Marketing and for analysis of websites.


The fact that computer software can learn independently has many implications. However, even though the technology has come a long way, this type of algorithmic calculation still requires the actions of humans. One could understand machine learning as a type of human computer interaction, because before the software can act and find solutions independently, it has to be given the relevant data. Moreover, certain regulations have to be established.

Types of Machine Learning[edit]

For machine learning, recurring types of algorithms are usually used.

  • Supervised learning: algorithms are defined on the basis of certain examples. The aim is to find solutions to problems through the generalization of a solution. Supervised learning can be used for example to expose credit card fraud.
  • Unsupervised learning: algorithms are edited with variable examples. The aim is to recognize a structure inside the dataset. This method is often used in so-called Clustering.

The above-mentioned methods can be combined with each other in what is called semi-supervised learning.

  • Transduction: the aim is to find new solutions on the basis of specific cases.
  • Learning to learn: this method is particularly exciting because the algorithms here draw derivatives from previous experiences.
  • Developmental learning: this level of machine learning attempts to develop the independent learning of software through exchange with human “teachers”.

Possibilites of use[edit]

Machine learning is used in the following areas of the internet:

Spam Filter[edit]

In this case, computer programs can develop and use their own filters for spam-mails or spam-messages through independent learning

Search Engine rankings[edit]

Machine learning in search engines can ensure that the relevance of websites to certain search terms is recognized independently.

Predicting user behavior[edit]

Independently acting algorithms can predict the search intention of users and accordingly customize the SERP or give recommendations for certain products in online shops.

Natural Language Processing[edit]

Lots of search engines such as google can also search for recorded terms. Machine Learning can be deployed here.

Fighting crime[edit]

Through algorithms analyzing different data, machine learning can expose for example credit card fraud or click fraud.

Significance for web analysis and marketing[edit]

Web analysis by means of machine learning has the advantage that big datasets such as big data are gathered and can be interpreted reliably. At the same time, data sets can be edited with further methods like Clustering or Data Mining.

A significant advantage of Machine Learning for website analysis can also be seen in the form of major time saving and the high efficiency of computers following certain rules which they then expand independently. Aside from website analysis, machine learning can also be deployed for online advertising.

The biggest weakness of machine learning lies in the actions of the people who lay out the algorithms.

Web Links[edit]