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In this 2 hour-long project, you will learn how to approach an image classification task using TensorFlow. You will learn how to effectively preprocess your data to improve model generalizability, as well as build a performant modeling pipeline. Furthermore, you will learn how to accurately evaluate model performance using a confusion matrix; how to interpret results; and how to ask poignant questions about your dataset. Finally, you will fine-tune an existing, state-of-the-art-ready model to improve performance further.
Note: This course works best for learners who are based in the North America region. We’re currently working on providing the same experience in other regions.
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1 - 2 von 2 Bewertungen für Fine-tuning Convolutional Networks to Classify Dog Breeds
von Yaron K
•22. Mai 2021
An extended example of how to preprocess data for a CNN, and then build the CNN or use transfer learning to create an image classification model. The complete notebooks are in the project resource section - so you can concentrate on listening to the lecturer and on annotating the code.
von Lasal J
•1. Juni 2021
The Course was not what I expected, the code didn't work and I had to search in stack overflow over and over again. UNPLEASENT EXPERIENCE!!!!!
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