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What is Machine Learning

 Machine learning is the ability of machines (i.e. computers) to learn from the data (or information) without being explicitly programmed. Machine learning is the most important part of the artificial intelligence. It enables the computers to learn from the information which is very important for artificial intelligence.

According to Tom M. Mitchell the formal definition of Machine learning can be,

A computer program is said to learn from experience E with respect to some class of tasks T and performance measures P if its performance at tasks in T, as measured by P, improves with experience E.

Machine learning is the product of research in pattern recognition and computational learning theory for building artificial intelligence programs. It uses same technique as data mining, except for one thing, it uses data for its own use instead of presentation to organization or individuals.

Machine learning can also be called as predictive analysis. Because it processes the given data and according to that data it predicts next step or the action to be taken according to the given situation. It is very helpful for stock market. Most of the people/companies use it for the same purpose. In today’s information abundance era, machine learning is very useful.

There are mainly 3 types of machine learning method:

  • Supervised learning: Computer is presented with input and its output. The task of computer here is to find the pattern by mapping input to output.
  • Unsupervised learning: Only input is given to the computer, leaving computer on its own to find the pattern or structure in data.
  • Reinforcement learning: In this kind of learning, computer performs its jobs and it gets feedback in the form of rewards or punishment. This type of learning is mainly used in computer games.

Machine learning is widely used now a days, some of the areas are as follows:

  • Search engines: i.e. google
  • Social networking sites: i.e. facebook
  • Plagiarism detection: i.e. online tests, content checking
  • Speech recognition
  • Image classification
  • Bio-science i.e. genetics
  • Spam detection i.e. in emails

These are only some examples, the machine learning has a very wide horizon and it is still evolving.

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