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Image Data Augmentation with Keras

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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.

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Unlock the potential of your image data with the "Image Data Augmentation with Keras" course, designed for IT and Computer Science enthusiasts. This engaging 1.5-hour project-based course guides you through the essential techniques of image data augmentation using Keras, a powerful neural network library. Tailored for intermediate learners, the course offers a hands-on approach to enhance your skills in data preprocessing and model training. Presented by Coursera, this free course is perfect for those looking to deepen their understanding of machine learning and artificial intelligence applications. Dive into the comprehensive content and elevate your expertise in transforming and augmenting image datasets to improve your model's performance. Join now and take your data science capabilities to the next level!