An Overview of machine learning

At this point, you must have heard of machine learning and artificial intelligence, or maybe you may have heard somebody speaking about opting for a machine learning course in Chennai. Whatever may be the case, this term has become extremely popular amongst the youth everywhere. Even though many people are aware of what exactly artificial intelligence is, some people are still confused about what machine learning is. It is pretty understandable as compared to artificial intelligence; it is a slightly lesser heard term; hence not many people know exactly what it is in what it does. This article will help you understand machine learning and how it can be applied in a prevalent industry such as AI.

To put it simply, machine learning is a sub-part of artificial intelligence that handles the Uses of algorithms and data to help a machine learn gradually, like a human, and improve its accuracy in many aspects. Historically speaking, what are the most famous example of machine learning is of Robert Nealey, Who was the master at the game of checkers; he played against an IBM computer in the year 1962 and lost. Comparing it to the wonders machine learning does today may not seem like a lot, but it Was one of the most significant feats achieved in the world of artificial intelligence and machine learning.

No, that you understood what exactly machine learning is, perhaps you may like a broken-down version of how machine learning works:

First comes the decision-making process of machine learning. Essentially the algorithms are used to make a classification or calculated prediction. The algorithm estimates a pattern within the actual data based on some labelled or unlabeled input data.

Up next comes the error functioning. The error function system tends to scrutinise the prediction made by The model. Suppose there are examples available according to the forecast made. In that case, the machine can quickly assess the given sample to cross-reference whether the prediction is absolutely accurate.

Finally comes the Model optimisation process. Within this, if the model can quickly Go hand in hand with the data points within the example set, then values are re-adjusted to reduce the differences between the example and the Estimate taken out by the machine. Essentially the machine keeps on doing this process of revaluation and Optimization, Constantly changing values until an answer with a particular amount of accuracy is conceived.

There also exist many examples in this modern world that we overlook daily; some of them are:

Speech recognition. This is one of the most popular usages of machine learning within modern systems. A famous example is the speech-to-text feature that is commonly available on multiple devices across a typical household. This feature is also used in specific artificial intelligence systems such as Google Assistant, Siri, etc.

Another famous example is customer service, and if you have visited some websites of the Other, you will notice that there are specific chat options available. These are essentially chatbots with which you Converse and record your response, according to which they give you an automated response from the list of answers they have available.


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