Data augmentation
12+ Data Augmentation Techniques for Data-Efficient ML
Data augmentation techniques generate different versions of a real dataset artificially to increase its size. Computer vision and natural language processing (NLP) models use data augmentation strategy to handle with data scarcity and insufficient data diversity. Data-centric AI/ML development practices such as data augmentation can increase accuracy of machine learning models.
Apr 103 min read
What is Data Augmentation? Use Cases & Examples
The performance of most ML models, and deep learning models in particular, depends on the quality, quantity and relevancy of training data. However, insufficient data is one of the most common challenges in implementing machine learning in the enterprise. This is because collecting such data can be costly and time-consuming in many cases.
Oct 266 min read