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Fruit-Classification-implement-TF-lite

Final Project Dicoding : Image Classification Model Deployment

Clasification of 33 types of fruits using sequential Tensorflow model and Conv2D Maxpooling Layer. This dataset consists of 16854 images with a division of 80% train data and 20% test data.Overall after training has a train accuracy of> 92% and validation accuracy> 92%. This shows that the model created is a good fit and in the final stage the model is saved into TF-Lite format.

CERTIFICATE BELAJAR PENGEMBANGAN MACHINE LEARNING