16 05

Brief explanation by Nadia Zaifulizan

Machine Learning comprises of systems or computers which are given the abilities to learn and improve from the experience of capturing and processing data.

It does so automatically without being specifically programmed to do so.

The more data the system processes, the more the system learns, and the more it improves its decision-making, classification, and predictions.

The ‘brain’ behind Machine Learning is its algorithm. The components of its algorithm focus on 3 area: 

  1. How input/knowledge is represented in a way that the computer algorithm can understand.
  2. The evaluation/utility function that evaluates the effectiveness of the algorithm used.
  3. The search method/technique that finds the ideal model/classifier with the best score.

With Machine Learning, a computer processes data, learns from it, makes decisions, and programs itself for future data. Its aim is such that in the near future, it can successfully interpret data that it has never processed before.

Machine Learning can also be utilized for business. With Machine Learning, businesses can monitor large incoming and outgoing data related to routine business processes, customer needs, and brand reputation.

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