November 2019
Intermediate to advanced
296 pages
7h 52m
English
Content preview from Hands-On Machine Learning with TensorFlow.js
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Image classification application
Let's see how it works by creating an image classification application with the MobileNet model. As we have already seen, MobileNet is a lightweight model designed for image classification tasks on edge devices. The model was invented by Google in 2017. As it tries to solve the trade-off problem between efficiency and accuracy, it achieves optimal model fitting in resource-constrained environments such as mobile devices without losing much accuracy. TensorFlow.js is categorized as the framework running on the edge device. MobileNet matches the primary use cases of TensorFlow.js.
First, we need to install the model via npm. You can do this using npm install @tensorflow-models/mobilenet or yarn add @tensorflow-models/mobilenet ...
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