Underfitting or Overfitting
How much data is enough. 100, 1000, 10000?
Underfitting is when the model is too simplified to know the base structure of data. It has too little information to construct an accurate training model.
Overfitting is where researchers overgeneralise and hope the machine can produce insight by the end of the training.
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While there are still challenges with Artificial Intelligence, we should not underestimate what AI can do. We know there are still many uncharted areas to be discovered in the coming years.
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