This tutorial shows how to fine-tune TensorFlow’s DeepLabV3 with a MobileNetV2 backbone using Model Garden. You’ll load Oxford-IIIT Pets via TFDS, convert samples to TFRecords, initialize from a pre-trained checkpoint, adjust experiment configs (classes, input size, batch, optimizer), train/evaluate with a mirrored strategy, and export the trained model for serving. It’s a practical, reproducible path from dataset prep to SavedModel.