13 Best practices for the real world
This chapter covers
- Hyperparameter tuning
- Model ensembling
- Mixed-precision training
- Training Keras models on multiple GPUs or on a TPU
You’ve come far since the beginning of this book. You can now train image classification models, image segmentation models, models for classification or regression on vector data, time-series forecasting models, text classification models, sequence-to-sequence models, and even generative models for text and images. You’ve got all the bases covered.
However, your models so far have all been trained at a small scale—on small datasets, with a single GPU—and they generally haven’t reached the best achievable performance on each dataset we looked at. This book is, after all, ...
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