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What are the possible reasons for an AI model not being efficient? Explain.

Topic - Project Cycle 

Type - Short answer 

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Reasons of an AI model not being efficient:

1. Lack of Training Data: If the data is not sufficient for developing an AI Model, or if the data is missed while training the model, it will not be efficient.

2. Unauthenticated Data / Wrong Data: If the data is not authenticated and correct, then the model will not give good results.

3. Inefficient coding / Wrong Algorithms: If the written algorithms are not correct and relevant, Model will not give desired output. Not Tested: If the model is not tested properly, then it will not be efficient.

4. Not Easy: If it is not easy to be implemented in production or scalable.

5. Less Accuracy: A model is not efficient if it gives less accuracy scores in production or test data or if it is not able to generalize well on unseen data.


Study more about Project cycle at Project Cycle Class 10

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