AgaMiko/data-augmentation-review
List of useful data augmentation resources. You will find here some not common techniques, libraries, links to GitHub repos, papers, and others.
This resource helps machine learning practitioners expand their datasets by providing a curated list of techniques and tools for data augmentation. It organizes a wide array of methods for various data types, from images and text to audio and time series, and links to relevant open-source libraries, academic papers, and other materials. Anyone building or training machine learning models who needs to increase their dataset size or improve model robustness will find this useful.
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Use this if you need to find strategies and tools to artificially expand your training datasets for machine learning models across different data types.
Not ideal if you are looking for a plug-and-play software tool for immediate data augmentation without exploring different options or understanding the underlying techniques.
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