This segment introduces the fundamentals of Keras through hands-on experiences with the Spotify dataset, covering everything from layer configuration and model creation to compilation, data preprocessing, and training.
The regularization module, utilizing the Mushrooms dataset, addresses the critical issues of overfitting and underfitting, explaining the concept of regularization and its importance in model training.
Exploring cutting-edge methodologies, this section delves into the Diamonds dataset to uncover the intricacies of optimizers, learning rate adjustments, TensorFlow Datasets, data generators, and advanced modeling techniques like non-sequential models, transfer learning, and multitask learning in a comprehensive overview.