Predictive Analytics with TensorFlow 7.2: Fine-tuning DNN Hyperparameters

The video tutorial covers hyperparameters in neural networks, focusing on their role in predictive analytics. It explains classification problems, performance metrics like precision, recall, and ROC curves, and discusses fine-tuning hyperparameters using methods like grid search. The tutorial also covers regularization techniques such as L2, L1, and dropout to prevent overfitting in deep neural networks.

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