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What is Machine Learning? We explain the background
The term Machine Learning has gained popularity and spread in the context of Artificial Intelligence. Our guide explains what Machine Learning actually describes and why it is so important.
Machine Learning means the improvement of Artificial Intelligences through learning processes.
Machine Learning translates to Machine Learning. In German-speaking countries, both terms are used comparably often, often depending on the direct environment.What is Machine Learning and what is the goal?
The properties of Machine Learning can be roughly summarized as follows:- Machine Learning describes the ability of Artificial Intelligence to improve itself.
- In this process, knowledge is generated artificially in order to increase the system's wealth of experience. The individual learning elements are subsequently generalized, which helps the artificial intelligence to independently apply what it has learned to new content in the future.
- It is important to distinguish between explicit (symbolic) and implicit (non-symbolic) approaches. The latter do not provide insight into the solution mechanisms that the system applies.
- Machine learning always takes place on the basis of algorithms. The process thus follows a defined sequence in a stepwise and structured manner.
- Equally important are the levels of supervision: machine learning can take place in a supervised or unsupervised manner, but also in a partially supervised manner. In addition, there is active and reinforcement learning. The latter works with incentives through rewards, which is similar to the human learning principle.
