What is machine learning?

What is machine learning?

Machine learning is a branch of artificial intelligence and is based on the idea that systems can learn from data, recognize patterns and make decisions on their own- with minimal human intervention. By identifying patterns in existing databases, IT systems can use algorithms to independently find solutions to problems rather than being programmed for the tasks. The larger the amount of data that the algorithms can access, the more they learn.

We encounter examples of the use of machine learning everywhere in everyday life. Think of the personalized recommendations for products on Amazon, facial recognition on Facebook or suggestions for the fastest route on Google Maps.

How does machine learning work?

 In principle, machine learning is based on human learning. A person learns by differentiating and repeating activities. Repeatedly showing multiple objects can help a person to distinguish them from other objects. Machine learning also follows a comparable approach. The commands of a programmer and a corresponding data input enable a computer to recognize and differentiate between different objects. The provision of suitable data plays a special role in this learning process. In the course of the learning process, the system can also learn the difference between a person and another object and thus make decisions based on this knowledge.

Different types of machine learning:-

Machine learning can be divided into the following categories:

Supervised learning: In supervised learning,  the machine is initially fed with sample inputs and outputs to train the system in the context of successive arithmetic operations with different inputs and outputs. In the course of the learning phase, the programmer provides the appropriate values ​​for individual entries and thus contributes to the learning process. In the end, the system is given the opportunity to identify relationships in data.

Unsupervised learning: In unsupervised learning, no sample inputs are defined before the learning process. The algorithm tries to differentiate and structure the existing data according to independently identified characteristics.

Partially supervised learning: Partially supervised learning is a mixture of Supervised learning and Unsupervised learning .

What are the areas of application for machine learning?

The range of applications for machine learning is almost limitless.  Machine learning is designed to help people work more efficiently and have more space to be creative. For example, the technology supports the organization and management of large databases or takes on stupid and repetitive tasks. Machine learning can also help people prepare data by helping to prepare, store and store paper documents.

Self-learning machines have the potential to take on particularly complex tasks. This includes, for example, identifying errors or predicting future damage. Especially in medicine, this approach opens up unimagined applications and contributes to the improvement of treatment methods. The real focus of machine learning is on the evaluation and processing of large amounts of data.

Conclusion

Machine learning is a mega trend and is currently enjoying the interest of the digital world. Above all, the increasing relevance of big data has given machine learning a powerful boost. Streaming providers Netflix and Amazon in particular use machine learning to optimize their own product range. The social network Facebook uses machine learning to mark people on uploaded pictures. The relevance of websites for certain search terms can be determined by machine learning. Machine learning can also differentiate between natural persons and bots in internet activities. In order to avoid the interaction of bots, the technology can identify bots on the basis of their patterns and prevent further interaction. Finally, the digital language assistants also use machine learning for speech and text recognition. In the financial sector in particular, the technology can be used to prevent fraud. Ultimately, machine learning is the only way to make large amounts of data categorizable, assessable and sortable depending on the context by quickly identifying patterns.