Maximizing the Impact of Data Augmentation: Effective Techniques and Best Practices

Author(s): Youssef Hosni

Originally published on Towards AI.

Data augmentation is a popular technique in machine learning that involves creating new data from existing data by making various modifications to it. These modifications could include adding noise, flipping images horizontally, or changing colors, among others. Data augmentation is an effective way to increase the size of a dataset and improve the performance of machine learning models.

However, data augmentation is not a one-size-fits-all solution. To maximize its impact, it is important to use effective techniques and best practices. In this article, we will explore some of the best practices for data augmentation and provide practical examples of how to…Read more

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Published via Towards AI