Introduction to PyTorch for Image Classification
Explore how to use PyTorch for image classification by preparing datasets, building and training neural networks, applying fine-tuning techniques, and conducting inference. Understand key steps like data splitting, augmentation, loss calculation, and model evaluation to develop robust image classification models.
We'll cover the following...
We'll cover the following...
We will learn how to write code to prepare our dataset and train our model to obtain the final weights and use it during inference in the next step. The flow is shown below:
Flow of the chapter
Data preparation
Data preparation is required to obtain the appropriate format of the data and send it through the model during training. For this purpose, we will learn how to:
- Split the dataset into train, test, and validation