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What are the five limitations of machine learning?

What are the five limitations of machine learning?

Do not learn incrementally or interactively, in real-time. Poor transfer learning ability, reusability of modules, and integration. Systems are opaque, making them very hard to debug. Performance cannot be audited or guaranteed at the ‘long tail’

What are disadvantages of machines?

Machines are expensive to buy, maintain and repair. Machine with or without uninterrupted use will get broken and worn-out. Their maintenance or repairs are costly, difficult to set up and operate without previous training. The pollution caused by machine increases, generating waste, augmenting power or oil use.

Which of the following is not an Machine learning Strategy in Ans?

Which of the following is not an Machine Learning strategies in ANNs? Explanation: Supreme Learning is not an Machine Learning strategies in ANNs. 14.

Which among the following are frequently faced issues in machine learning?

7 Major Challenges Faced By Machine Learning Professionals

  • Poor Quality of Data.
  • Underfitting of Training Data.
  • Overfitting of Training Data.
  • Machine Learning is a Complex Process.
  • Lack of Training Data.
  • Slow Implementation.
  • Imperfections in the Algorithm When Data Grows.
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What are the disadvantages of machine language?

Machine Language

Advantages Disadvantages
Machine language makes fast and efficient use of the computer. All operation codes have to be remembered
It requires no translator to translate the code. It is directly understood by the computer. All memory addresses have to be remembered.

What are the pros and cons of using a machine?

Advantages and Disadvantages of the Use of Machinery

  • The following are the chief advantages of the use of machinery:
  • Use of Natural Forces:
  • Heavy and Delicate Work:
  • Faster Work:
  • More Accurate Work:
  • Strain on:
  • Cheap Goods:
  • Mobility of Labour: