- Machine Learning (ML)
- Typen von Maschinellem Lernen
- Aufgabenstellungen des „Machine Learning“
- Anwendungsgebiete des „Machine Learning“
- Kategorien des „Machine Learning“
Machine Learning (ML)
Meanwhile intelligent machines are indispensable in our everyday lives. In many areas, they help people, to make better decisions. By “machines” is meant computer systems and their software, not traditional machines in production halls.
But how does Machine Learning works? It simply means, computers are taught how to analyse data. Machines examine and scan data to identify patterns and to apply them to familiar rules:
- categorize people or things
- predict likely outcomes
- identify unknown patterns and relationships
- recognize unusal or unexpected behaviours
With “Machine Learning Algorithms” computers learn independently. Algorithms are the processes the machines use for learning. For example, when new data is delivered to the machine due to an environmental change, the performance of the algorithm improves. This causes, that the “intelligence” of the machine is increasing. In this way the machine is constantly learning.
Are machines creative or intelligent?
Since the begin of Big Data, the amount of available data as well as the abilty to process the data, increased exponentially. Also, the intelligence and the learning ability of the machines are grown proportionately. Large amounts of data can be analysed within a very short time and the system can derive resulting measures. Machine Learning offers new ways to solve problems.
Nevertheless, machines are not yet autonomous and independent in their intelligence and creativity.
A machine cannot set up and develop new hypotheses from unassigned facts or data. Further, the machine is not able to find new ways and solutions to respond to recurring appeals.
Summing up, the outcome of a machine learning algorithm depends entirely on the data, to which it is exposed. If the data changes, the results also change.
The Medical Case Appas example for Machine Learning
Today Machine Learning can greatly simplify everyday life. This will be briefly explained using the example of the Medical Case App.
This app stores all health-relevant data of the users in the user profile. The data can always be adapted to the current health situation, e.g. if a pacemaker is needed or a pregnancy is pending. Data about the medication are scanned and stored via a barcode. Through numerous application possibilities the user benefit from the artificial intelligence of the app.
By choosing between four different search methods the user receives a list of results with all medicals, that fit his search. From this list items can be selected and provided with personal attributes, such as: time, appointment, routine etc.
If the health situation changes, the settings of taking drugs can quickly and easily be adjusted. Users can set their own appointments, such as reminder notes or purchase reminders. In addition, users receive notifications and alerts when a product is no longer available in the store or taking a medical has been forgotten. All health-related data are visible for the user at a glance. Especially for older people, the Medical Case App can make their life a lot easier. No longer they need to worry about their medications themselves. This is done by the app.
In an emergency the app can also save lives, because the emergency doctor has immediately all health data available.