Browser-based Models with TensorFlow.js

所在平台: CourseraArchive

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大学或机构: CourseraNew

课程主页: https://www.coursera.org/archive/browser-based-models-tensorflow

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课程大纲

Introduction to TensorFlow.js
Image Classification In the Browser
Converting Models to JSON Format
Transfer Learning with Pre-Trained Models

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Bringing a machine learning model into the real world involves a lot more than just modeling. This Specialization will teach you how to navigate various deployment scenarios and use data more effectively to train your model. In this first course, you’ll train and run machine learning models in any browser using TensorFlow.js. You’ll learn techniques for handling data in the browser, and at the end you’ll build a computer vision project that recognizes and classifies objects from a webcam. This Specialization builds upon our TensorFlow in Practice Specialization. If you are new to TensorFlow, we recommend that you take the TensorFlow in Practice Specialization first. To develop a deeper, foundational understanding of how neural networks work, we recommend that you take the Deep Learning Specialization.

使用TensorFlow.js的基于浏览器的模型:将机器学习模型带入现实世界不仅仅涉及建模。本专业知识将教您如何导航各种部署方案并更有效地使用数据来训练模型。 在第一门课程中,您将使用TensorFlow.js在任何浏览器中训练和运行机器学习模型。您将学习在浏览器中处理数据的技术,最后将建立一个计算机视觉项目,该项目可以识别和分类来自网络摄像头的对象。 该专业化基于我们的TensorFlow实践专业化。如果您不熟悉TensorFlow,我们建议您首先参加TensorFlow实践专业化课程。为了对神经网络的工作方式有更深入的基础了解,我们建议您参加“深度学习专业化”课程。

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