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Learning Tensorflow.js with Gant Laborde
Media Type |
audio
Categories Via RSS |
Technology
Publication Date |
Nov 09, 2021
Episode Duration |
00:51:21

Machine learning models must first be trained.  That training results in a model which must be serialized or packaged up in some way as a deployment artifact.  A popular deployment path is using Tensorflow.js to take advantage of the portability of JavaScript, allowing your model to be run on a web server or client. Gant

The post Learning Tensorflow.js with Gant Laborde appeared first on Software Engineering Daily.

Machine learning models must first be trained.  That training results in a model which must be serialized or packaged up in some way as a deployment artifact.  A popular deployment path is using Tensorflow.js to take advantage of the portability of JavaScript, allowing your model to be run on a web server or client. Gant

Machine learning models must first be trained.  That training results in a model which must be serialized or packaged up in some way as a deployment artifact.  A popular deployment path is using Tensorflow.js to take advantage of the portability of JavaScript, allowing your model to be run on a web server or client.

Gant Laborde is Chief Innovation Officer at Infinite Red, a React Native consulting team and the author of Learning TensorFlow.js: Powerful Machine Learning in JavaScript from O’Reilly.  In this interview, we explore use cases for Tensorflow.js.

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The post Learning Tensorflow.js with Gant Laborde appeared first on Software Engineering Daily.

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