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What is machine learning - ML definition and application examples

What is machine learning - ml definition and application examples, In recent times, artificial intelligence has captured the attention of the entire world? It has become the most important discussion on the dialogue tables about what the world seeks to achieve in terms of technological development and unprecedented progress. Indeed, this interest was not in vain; Many models have appeared that confirm that artificial intelligence has come close to competing with human intelligence, and we have noticed this with the creation of self-driving cars, the Sophia robot, and many others, and with this success after another, the area of ​​interest has increased more in what is known as machine learning and its development to move forward towards successes Greater in employing artificial intelligence, but what is machine learning and what is its importance and principle of work?

What is machine learning - ML definition and application examples

What is machine learning?

(Machine Learning), abbreviated as (ML), the concept of machine learning can be simplified as one of the branches of artificial intelligence (AI) based on programming computers of various forms to be able to carry out commands and perform the tasks assigned to them based on the existing data and their analysis while restricting Human intervention in directing it or completely absent.

It is noteworthy that the term machine learning appeared by the pioneer of artificial intelligence Arthur Samuel in 1959 within the scope of the work of (IBM) laboratories. In the end, the role of the human element is very small. It will also be the responsibility of the machine to make the decision when needed, and determine what tasks should be performed, when, how, and why without any human help at all, as this will certainly contribute to completing the tasks as quickly as possible compared to the time that humans consume to complete the tasks.

Machine learning principle

It may seem complicated at first about how a machine learns and how feasible it is; however, this is not impossible at all, as many practical applications of artificial intelligence based on the principle of machine learning have emerged, the most famous of which is the robot, Sophia. With regard to the principle of work, algorithms are the basis for the application of machine learning, as these algorithms consist of a series of commands, instructions, and instructions necessary to direct the machine or computer to how the tasks should be carried out, as the algorithms play the role of the mastermind in the machine due to its polarization of data. and collecting and analyzing them, and ultimately relying on the analyzed data to determine how the task should be carried out.

The algorithms used in machine learning rely on a set of graphic models and decision tools such as decision trees, natural language processing, and artificial neural networks to automate the data analysis and processing; thus motivating the machine to make a decision and carry out the tasks assigned to it with ease and ease. It must be pointed out that the artificial neural networks used in machine learning play a very important role that is comparable to the role of nerves and their networks in the human body and brain (deep learning).

The relationship between machine learning, artificial intelligence, and data collection

The dimensions of the relationship between artificial intelligence, machine learning, and data mining can be drawn in the form of 3 umbrellas of varying size; Where the science of artificial intelligence is considered the largest umbrella that includes directly under it the umbrella of machine learning, while the latter embraces the umbrella of data mining and extraction. Ultimately relying on different methods of decision-making and thinking.

As for (Machine Learning), it represents the role of the layer that follows the top of the pyramid, and its role is to implement the task of automation and programming and teach machines to use the data available to them in decision-making, and here appears the role of (Data Mining) by searching for relevant data and using it to perform the task.

How important is machine learning?

The branch of machine learning has been able to gain great importance in the modern era, specifically after the tremendous developments that have occurred in artificial intelligence and its algorithms, and its importance is as follows:

  • Providing a large amount of data necessary for decision-making.
  • The ability to store data as much as possible.
  • Computerized data processing is less financially costly than employing human hands.
  • Analyze the largest amount of data at its various levels, whether simple or complex.
  • Ensuring more accurate results and decisions in the fastest time.
  • Enabling organizations and various establishments to monitor the most appropriate opportunities to achieve profits and avoid unknown dangers.
  • Assistance in choosing the optimal decision from a range of available alternatives.