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所在平台: Coursera专项课程 课程类别: 其他类别 大学或机构: CourseraNew |
课程主页: https://www.coursera.org/specializations/tensorflow-data-and-deployment
课程评论：没有评论
课程名称：TensorFlow：数据和部署专业化 课程概述： 在此四门课程的专业化中，学员将继续在TensorFlow中扩展他们的技能，学习如何在各种部署场景中有效使用数据，以更好地训练模型。课程内容包括如何在浏览器和移动应用程序中训练及运行机器学习模型，利用内置数据集、API进行数据处理和拆分，以及如何处理各种非结构化数据。学员将应用所学知识于多种部署情境，并介绍TensorFlow Serving、TensorFlow Hub、TensorBoard等重要工具。 随着全球各行业对人工智能的不断采用，由Laurence Moroney和Andrew Ng主讲的这门专业化将帮助学员更快、更准确地在任何设备或平台上开发和部署机器学习模型。建议学习者在注册此专业化前，先完成“TensorFlow实践专业”。 课程包括： 1. 使用TensorFlow.js构建浏览器模型 - 课程链接：[浏览器模型](https://www.coursera.org/learn/browser-based-models-tensorflow) 2. 使用TensorFlow Lite构建设备模型 - 课程链接：[设备模型](https://www.coursera.org/learn/device-based-models-tensorflow) 3. 使用TensorFlow数据服务构建数据管道 - 课程链接：[数据管道](https://www.coursera.org/learn/data-pipelines-tensorflow) 4. 使用TensorFlow处理高级部署场景 - 课程链接：[高级部署场景](https://www.coursera.org/learn/advanced-deployment-scenarios-tensorflow) 借助此专业化，学习者将能够更有效地将他们的机器学习模型应用于现实世界中的各种设备。
Course Link: https://www.coursera.org/learn/browser-based-models-tensorflow
Name:Browser-based Models with TensorFlow.js
Description:Offered by DeepLearning.AI. Bringing a machine learning model into the real world involves a lot more than just modeling. This ... Enroll for free.
Course Link: https://www.coursera.org/learn/device-based-models-tensorflow
Name:Device-based Models with TensorFlow Lite
Description:Offered by DeepLearning.AI. Bringing a machine learning model into the real world involves a lot more than just modeling. This ... Enroll for free.
Course Link: https://www.coursera.org/learn/data-pipelines-tensorflow
Name:Data Pipelines with TensorFlow Data Services
Description:Offered by DeepLearning.AI. Bringing a machine learning model into the real world involves a lot more than just modeling. This ... Enroll for free.
Course Link: https://www.coursera.org/learn/advanced-deployment-scenarios-tensorflow
Name:Advanced Deployment Scenarios with TensorFlow
Description:Offered by DeepLearning.AI. Bringing a machine learning model into the real world involves a lot more than just modeling. This ... Enroll for free.
Continue developing your skills in TensorFlow as you learn to navigate through a wide range of deployment scenarios and discover new ways to use data more effectively when training your model. In this four-course Specialization, you’ll learn how to get your machine learning models into the hands of real people on all kinds of devices. Start by understanding how to train and run machine learning models in browsers and in mobile applications. Learn how to leverage built-in datasets with just a few lines of code, use APIs to control how data splitting, and process all types of unstructured data. Apply your knowledge in various deployment scenarios and get introduced to TensorFlow Serving, TensorFlow, Hub, TensorBoard, and more. Industries all around the world are adopting AI. This Specialization from Laurence Moroney and Andrew Ng will help you develop and deploy machine learning models across any device or platform faster and more accurately than ever. This Specialization builds upon skills learned in the TensorFlow in Practice Specialization. We recommend learners complete that Specialization prior to enrolling in TensorFlow: Data and Deployment.
TensorFlow：数据和部署专业化：在学习导航各种部署方案并发现训练模型时更有效地使用数据的新方法时，请继续在TensorFlow中发展技能。 在这四门专业课程中，您将学习如何将机器学习模型带入各种设备上的真实人的手中。首先了解如何在浏览器和移动应用程序中训练和运行机器学习模型。了解如何仅用几行代码就可以利用内置数据集，如何使用API控制数据拆分的方式以及如何处理所有类型的非结构化数据。将您的知识应用到各种部署场景中，并被介绍给TensorFlow Serving，TensorFlow，Hub，TensorBoard等。 世界各地的行业都在采用AI。 Laurence Moroney和Andrew Ng的本专业知识将帮助您比以往任何时候都更快，更准确地在任何设备或平台上开发和部署机器学习模型。 本专业建立在TensorFlow实践专业中学习的技能之上。我们建议学习者在注册TensorFlow：数据和部署之前先完成专业化培训。