In the first part, we looked at how we built a data pipeline required for creating data loaders using fastai. In this part, we will create different segmentation models that help us rank in the top 4% of the Kaggle Leader board.
When working on Deep learning projects getting the right pipeline starting from data processing to creating predictions is a nontrivial task. In the last few years, several frameworks were built on top of popular deep learning frameworks like TensorFlow and PyTorch to accelerate building these pipelines. In this blog, we will explore how we can use one of the popular frameworks fastai2 which is currently in the early release but the high-level API is stable for us to use.