Project: Basic Image Classification with TensorFlow

所在平台: CourseraArchive

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大学或机构: CourseraNew

课程主页: https://www.coursera.org/archive/tensorflow-beginner-basic-image-classification

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TensorFlow Beginner: Basic Image Classification

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In this 2-hour long project-based course, you will learn the basics of using Keras with TensorFlow as its backend and use it to solve a basic image classification problem. By the end of this project, you will have created, trained, and evaluated a Neural Network model that will be able to predict digits from hand-written images with a high degree of accuracy. You also will have learned the fundamentals of neural networks, TensorFlow, and Keras. This course runs on Coursera's hands-on project platform called Rhyme. On Rhyme, you do projects in a hands-on manner in your browser. You will get instant access to pre-configured cloud desktops containing all of the software and data you need for the project. Everything is already set up directly in your internet browser so you can just focus on learning. For this project, you’ll get instant access to a cloud desktop with Python, Jupyter, and Tensorflow pre-installed. Notes: - You will be able to access the cloud desktop 5 times. However, you will be able to access instructions videos as many times as you want. - This course works best for learners who are based in the North America region. We’re currently working on providing the same experience in other regions.

项目:使用TensorFlow进行基本图像分类:在这个基于项目的长达2小时的课程中,您将学习使用以TensorFlow作为后端的Keras的基础知识,并将其用于解决基本图像分类问题。在该项目结束之前,您将创建,训练和评估一个神经网络模型,该模型将能够从手写图像中高精度地预测数字。您还将学习神经网络,TensorFlow和Keras的基础知识。 本课程在Coursera的动手项目平台Rhyme上运行。在Rhyme上,您可以在浏览器中以动手方式进行项目。您将立即访问包含项目所需的所有软件和数据的预配置云桌面。一切都已经直接在您的Internet浏览器中设置,因此您可以专注于学习。对于此项目,您将可以立即访问预先安装了Python,Jupyter和Tensorflow的云桌面。 笔记: -您将能够访问云桌面5次。但是,您将可以根据需要多次访问说明视频。 -本课程最适合北美地区的学习者。我们目前正在努力在其他地区提供相同的体验。

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