Image Data Augmentation with Keras

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In this Guided Project, you will:

Image Data Augmentation with Keras

Using Image Data Generator with a Keras Model

Clock1.5 hours
IntermediateIntermediate
CloudNo download needed
VideoSplit-screen video
Comment DotsEnglish
LaptopDesktop only

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.

Skills you will develop

Deep LearningConvolutional Neural NetworkMachine Learningimage augmentationkeras

Learn step-by-step

In a video that plays in a split-screen with your work area, your instructor will walk you through these steps:

  1. Introduction and Importing Libraries

  2. Rotation

  3. Width and Height Shifts

  4. Brightness

  5. Shear Transformation

  6. Zoom

  7. Channel Shift

  8. Horizontal and Vertical Flips

  9. Data Normalization

  10. Rescale and Preprocessing Function

How Guided Projects work

Your workspace is a cloud desktop right in your browser, no download required

In a split-screen video, your instructor guides you step-by-step

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Frequently Asked Questions

More questions? Visit the Learner Help Center.