Question 1 of 30
A retail company is implementing Einstein Vision to enhance its product categorization process. They have a dataset of 10,000 images of various products, each labeled with their respective categories. The company aims to train a model that can accurately classify these images into 5 distinct categories. After training, they evaluate the model and find that it achieves an accuracy of 85%. If the company wants to improve the model\'s accuracy to at least 90%, which of the following strategies would be the most effective in utilizing Einstein Vision\'s capabilities?
Increase the dataset size by adding more labeled images and augmenting existing images to enhance diversity.
Adjust the model's hyperparameters without changing the dataset.
Use a different pre-trained model that is not specifically designed for image recognition tasks.
Reduce the number of categories to simplify the classification task.

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