I’m working on training an AI model, but I’m facing several challenges such as overfitting, data quality issues, and model performance. What are some of the key challenges you’ve encountered while training AI models, and how did you overcome them? Any tips on improving model accuracy and efficiency?
Based on your other post response, I get an understanding you are not new to AI.
can you mention what is the issue you are facing?
it can usually happen in a highly imbalanced data or not enough data and also how one creates a model based on their understanding of dataset one is working on.
Understanding the dataset is most important for me. how are the features/classes/data point distributed in dataset is another important point.
further you can always create a model, make changes and see how your model is doing better or poor for every variation in your parameters.
I don’t know if you have taken deep learning specialisation, but this specialisation covers overfitting, underfitting, bias, variance in detail.