In this hands-on project, we'll apply K-Nearest Neighbors algorithm to handwritten digit classification. Our main objectives are: a) to learn how to experiment with various hyper-parameters, b) introduce metrics classification accuracy and confusion matrix, c) develop intuition about how KNN works and d) use this intuition and data-augmentation to improve classification accuracy further.
Part of course:
Hands-on Project: Digit classification with K-Nearest Neighbors and Data Augmentation
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