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How Do The Machines Learn?

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A Brief Overview Of Machine Learning And Artificial Intelligence

Artificial intelligence (AI) is about a wide-ranging branch of computer science concerned with building smart machines capable of performing tasks that typically require human intelligence. Machine learning is a form of artificial intelligence wherein a machine “learns” by looking for patterns among massive data loads, and when it sees one, it adjusts the program to reflect the “truth” of what it found.

The more data you expose the machine to, the “smarter” it gets. And when it sees enough patterns, it begins to make predictions. Unlike humans, however, machines cannot generalize knowledge or transfer learning from one application to another. Due to this, the idea that Artificial intelligence (AI) will take over the world and decide the fate of humanity which many people hold is largely a misconception as AI in itself cannot formulate opinions or emotions.

However, this does not reduce the AI’s intelligence as it can still perform computations that will take data scientist’s months to come up with. When we talk of learning we have to realize its context in the modern world, before learning took place, problem-solving tasks relied on writing algorithms. A machine learning algorithm is simply a set of rules that takes an input and returns an output as a solution for the problem. Consider the following: Given a list of numbers, you are asked to sort them in increasing order. This problem is solved by algorithms. On the other hand, some problems were not so easy to solve by algorithms. A notable example of this problem is classification, where it is very difficult to write an algorithm that classifies unknown objects without an already assembled database which makes the task moot.

In this regard, machine learning and artificial intelligence can prove to be very useful. According to the, a computer learns “from previous computations to produce reliable, repeatable decisions and results”. In simpler terms, machine learning is the act of a computer creating its own database through the observation of existing data and therefore evolving the ability to make predictions on that. Data over time, essentially learning about said data. Machine learning project idea is not new. The term was first defined by back in 1959.