What Is Machine learning?

When we talk about machine learning than the main point which we hit in our mind is ” How you make your machine learn ?”
This is the scientific term that means the study of algorithms and statistical models that computer systems use to perform there task without using explicit instructions, relying on patterns and inference instead.

Machine learning algorithms work on the Mathematical data model which is based on sample data known as “Training Data” that helps to make predictions or decisions without being facing any issues.

Machine Learning algorithms are used in a wide variety of applications such as email filtering and so on, where it was difficult for the programmer to develop such type of algorithms.
It is closely related to computational statistics, which focus on making predictions using a computer.
The History of “Machine learning” starts in 1959 with IBM. Machine learning, reorganized as a separate field, started to flourish in the 1990s.

Benefits of Machine Learning :

  • Easily Identify trends and patterns.
  • No Human interventions needed.
  • Continuous improvement.
  • Wide applications.
  • Handling Multi-dimensional and multi-variety data.

Disadvantages of machine learning :

  • High Error Susceptibility.
  • Data Acquisition.
  • Interpretation of Results.
  • time and resources.

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