Training a Neural Network with Augmentation
Explore how to apply various image augmentation methods in PyTorch to expand training datasets and enhance model generalization. Understand techniques such as flipping, cropping, grayscale conversion, and blurring to improve the accuracy and robustness of neural networks in image classification tasks.
We'll cover the following...
Data augmentation is an important aspect of training machine learning models. This lesson will cover all the data augmentation classes in the PyTorch Image Model framework.
Data augmentation is a common technique used in machine learning to increase datasets. Typically, we modify the raw samples in multiple ways to create altered copies.
Let’s look at the following illustrations to understand more about data augmentation:
Benefits of data augmentation
Training a machine learning model requires a lot of labeled data, and it takes time to collect and label the datasets. The entire process can be tedious and costly.
Therefore, most ...