Image Classification with CNNs using Keras
Implement Convolutional Neural Networks in Keras with TensorFlow backend
Train Convolutional Neural Networks to solve Image Classification
In this 1-hour long project-based course, you will learn how to create a Convolutional Neural Network (CNN) in Keras with a TensorFlow backend, and you will learn to train CNNs to solve Image Classification problems. In this project, we will create and train a CNN model on a subset of the popular CIFAR-10 dataset. 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 (e.g. Python, Jupyter, and Tensorflow) pre-installed. Prerequisites: In order to be successful in this project, you should be familiar with python and convolutional neural networks. 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.
您要培养的技能
分步进行学习
在与您的工作区一起在分屏中播放的视频中，您的授课教师将指导您完成每个步骤：
Import Libraries
Preprocess Data
Visualize Examples
Create Model
Train the Model
Final Predictions
指导项目工作原理
您的工作空间就是浏览器中的云桌面，无需下载
在分屏视频中，您的授课教师会为您提供分步指导
审阅
来自IMAGE CLASSIFICATION WITH CNNS USING KERAS的热门评论
it was short n up to the mark, fully hands on and i came to know many new terms and their working. as it is a 1 hr assignment, this is just sufficient and satisfactory for beginners.
Really enjoyed learning from Amit Yadav. He promptly answers any query posted in the discussion forum. Looking forward to learning more from him.
if you have knowledge about CNN and Keras then it is good project as a practice and revision.
The project is good and the instructor explains the main areas of the code very well.
常见问题
常见问题
如果我购买指导项目，会得到什么？
购买指导项目后，您将获得完成指导项目所需的一切，包括通过 Web 浏览器访问云桌面工作空间，工作空间中包含您需要了解的文件和软件，以及特定领域的专家提供的分步视频说明。
指导项目可在台式设备和移动设备上学习吗？
由于您的工作空间包含适合笔记本电脑或台式计算机使用的云桌面，因此指导项目不在移动设备上提供。
指导项目的讲师是谁？
指导项目讲师是特定领域的专家，他们在项目的技能、工具或领域方面经验丰富，并且热衷于分享自己的知识以影响全球数百万的学生。
我能在完成指导项目后从中下载作品吗？
您可以从指导项目中下载并保留您创建的任何文件。为此，您可以在访问云桌面时使用‘文件浏览器’功能。
我能够退款吗？退款政策是如何规定的？
指导项目不符合退款条件。请查看我们完整的退款政策。
有助学金吗？
指导项目不提供助学金。
我能旁听指导项目并免费观看视频部分吗？
指导项目不支持旁听。
我需要具备多少经验才能做这个指导项目？
您可在页面顶部点按此指导项目的经验级别，查看任何知识先决条件。对于指导项目的每个级别，您的讲师会逐步为您提供指导。
我能直接通过 Web 浏览器来完成此指导项目，而不必安装特殊软件吗？
是，您可以在浏览器的云桌面中获得完成指导项目所需的一切。
指导项目的学习体验如何？
您可以直接在浏览器中于分屏环境下完成任务，以此从做中学。在屏幕的左侧，您将在工作空间中完成任务。在屏幕的右侧，您将看到有讲师逐步指导您完成项目。
还有其他问题吗？请访问 学生帮助中心。