Machine Learning

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Machine learning is a subfield of artificial intelligence. By recognizing patterns in existing data sets, IT systems are able to find independent solutions to problems.

Everybody knows it: You make a positive or negative experience, draw conclusions and base further decisions on these findings. The same principle can be found in machine learning. Here, data sets and algorithms are recognized by the IT systems and develop solutions from the patterns and regularities. Artificial knowledge, from artificial experience. And just like in humans, knowledge gained is generalised and used for new problem solutions or for analyses of previously unknown data. Easy or?

In the beginning it is necessary to supply the systems with the data and algorithms relevant for learning. Also rules, how the data stock is to be analyzed and which patterns are to be recognized, must be defined at the beginning. After all this preliminary work you will benefit from the following bars:

  • Relevant data is found, extracted and summarized
  • Predictions are made on the basis of the analysed data
  • Probabilities for the occurrence of certain events are calculated
  • Independent adaptation to developments
  • Processes are optimized on the basis of the detected patterns

The different types of Machine Learning

We now know that algorithms can recognize patterns and generate suitable solutions. However, these algorithms can be divided into different learning categories:

  • Supervised Learning
  • Unsupervised Learning
  • Semi-supervised learning
  • Reinforcing learning¬†

In our next blog post, we will explain the learning categories in detail and give some noteworthy practical examples! Machine Learning has a very wide range of possible applications. If we take our homepage as an example, Machine Learning can help to detect spam mails and to develop suitable filters. A well developed IT system can also determine the relevance of websites for search terms. Social media channels attach great importance to distinguishing Internet activity from natural persons and bots.

Due to the development in the field of big data technology, machine learning has received an enormous boost. Because with their large amounts of data, they form the ideal basis. Machine learning algorithms work better the more input data exists.

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