GPN19:Client-side AI in JavaScript using Tensorflow.js: Unterschied zwischen den Versionen
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In practice, edge computing is becoming evermore important and workloads are moved away from the backend. Tensorflow.js enables you to run AI models completely in the browser, which is also great for data privacy because often there is no more need to transfer sensitive data to backend servers. | In practice, edge computing is becoming evermore important and workloads are moved away from the backend. Tensorflow.js enables you to run AI models completely in the browser, which is also great for data privacy because often there is no more need to transfer sensitive data to backend servers. | ||
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Aktuelle Version vom 30. Mai 2019, 13:54 Uhr
Ein Vortrag von Mathias Burger auf der GPN19.
In a practical example I will show you how to build a gesture classifier for a vertical scrolling browser game. Along the way, we will discuss the Tensorflow.js API and a specific model architecture called MobileNet.
In practice, edge computing is becoming evermore important and workloads are moved away from the backend. Tensorflow.js enables you to run AI models completely in the browser, which is also great for data privacy because often there is no more need to transfer sensitive data to backend servers.