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Machine Learning definition | What is Machine Learning

This page mentions machine learning definition and describes basic building blocks in machine learning. It mentions advantages, disadvantages and applications of machine learning.

Machine Learning definition: The subfield of computer science which uses algorithms to provide training to machines from input data (original and new set of data) to take action. The machine learning uses automation and iterative methods.

Following are the features or characteristics of machine learning.
• Machine learning based devices do not require to be explicitly programmed at the time of manufacturing.
• These machines use pattern recognition and artificial intelligence for their functional operation.
• These are like software programs which provides learning to themselves when they are exposed to new conditions and data.
• It takes better decision in real time without any human intervention.


Machine Learning

Figure-1 depicts Machine Learning Blocks. As shown any machine learning process has three parts viz. input, objective function and output.

Advantages and Disadvantages of Machine Learning

Advantages:
• Implementation and automation of machine learning is easy for machines unlike humans. Once learnt, machine can process millions of images or data without any issues unlike humans who can get fatigue and sometimes gets brain headache.

Disadvantages:
• Learning and writing algorithm is easy for humans while it is tough for machine.
• Machine need time and more data to accurately predict or classify.

Applications of Machine Learning

Following are the applications of machine learning.
• Self driving cars
• Effective web search with suggested ads as per users previous activity on the system.
• Speech recognition
• News feed part in the social media application e.g. facebook uses members activity in the past and their interest.
• Banking, telecom and retail sector has many applications.
• Diagnosis and prognosis as well as screening in Bio-medical sector.
• Face recognition, iris verification, finger printing in Biometric sector.
• Handwriting recognition and speech recognition in computer interfaces.
• Text translation in the internet field.

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