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學生對 Coursera Project Network 提供的 Image Data Augmentation with Keras 的評價和反饋

4.6
441 個評分
70 條評論

課程概述

In this 1.5-hour long project-based course, you will learn how to apply image data augmentation in Keras. We are going to focus on using the ImageDataGenerator class from Keras’ image preprocessing package, and will take a look at a variety of options available in this class for data augmentation and data normalization. Since this is a practical, project-based course, you will need to prior experience with Python programming, convolutional neural networks, and Keras with a TensorFlow backend. Data augmentation is a technique used to create more examples, artificially, from an existing dataset. This is useful if your dataset is small and you want to increase the number of examples. Data augmentation can often solve over-fitting so that your model generalizes well after training. For images, a variety of augmentation can be applied to increase the number of examples. Note: 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....

熱門審閱

AQ
2021年11月22日

The instructor, Amit Yadav, is very clear in his instruction and provide great explanation on his model building, and compiling. Definitely a great course to get some deep learning skills.

SJ
2020年4月17日

Perfect course for beginners, requires very little base to start. Highly recommend it, certainly worth the time. Do look into convolutional neural network briefly before you start.

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