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One of the most prominent challenges was to optimize and reduce the training time of the machine learning model, we used data augmentation to re-inforce the model's accuracy however it laid a toll on the time required for the training process. Eventually we were able to manage a reasonable trade-off and deliver an accurate and fast model.
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