Tier

Advanced

Professional-grade TensorFlow: reuse pretrained models, write custom training loops, and avoid the mistakes that hurt in production.

1. 1Transfer LearningTake a model pretrained on millions of images and fine-tune it on a tiny dataset in seconds, right in the browser.~30 min
2. 2Custom Training LoopsDrop `model.fit` and write the gradient tape by hand — inspect every gradient tensor as it flows backward.~30 min
3. 3Production Best PracticesConverting, shipping, and watching a model in production — quantization, versioning, training-serving skew, and drift.~30 min
4. 4TensorFlow Data Pipelinestf.data.Dataset, batching, shuffling, mapping, caching, and prefetching — feeding a model without starving it.~25 min
5. 5Keras Functional API, DeeperBeyond a single stack of layers: multi-input/output models, shared layers, and skip connections you can't build with Sequential.~25 min
6. 6Improving Your ModelsThe practitioner's toolkit: learning rate, batch size, capacity, dropout, augmentation, early stopping, and checkpoints.~30 min