Improving Your Model - Data Augmentation
There are situations, at times, where you would not be able to improve the accuracy of your model by building a better model. Sometimes, the problem is not the model but the data. One of the most important things to consider when working with machine learning is that the data you work with has to be good enough for a potential model to generalize that data.
Data can represent real-life things, but it can also include incorrect data that may perform badly. This can happen when you have incomplete data or data that does not represent the classes well. For those cases, data augmentation has become one of the most popular approaches.
Data augmentation actually increases the number of samples of the original dataset. For computer vision, this could mean increasing the number of images in a dataset. There are several data augmentation techniques, and you may want to use a specific technique, depending on the dataset. Some of these techniques are mentioned...
